How should a district heating network digitalization plan look in practice?

We previously covered the basics and importance of digitalization in district heating in the article: Digitalizing District Heating Networks – what it means and how to do it right?, which discussed the fundamentals of the digital transformation process.

In this article, we focus on the practical aspect of digitalization – showing step by step how the decision-making process unfolds: from the initial audit, through defining strategic goals and selecting technologies, to implementation, performance monitoring, and KPI analysis – and how to execute the planned roadmap.

What benefits does network digitalization bring to heating companies?

Modern measurement technologies and telemetry devices with remote communication – digital sensors, controllers, heat meters, thermometers, and flow meters, as well as hybrid substations enabling integration of renewable energy sources and real-time data transmission – give companies full insight into the condition of their networks. This enables remote reading, control, and optimization of the system in near real time, which translates into fewer breakdowns (predictive maintenance), lower operational costs, and greater reliability of supply.

Reading temperatures and controlling thermal comfort in consumer premises (with their participation) also leads to lower heat consumption and reduced bills.
Digitalization supports EU climate objectives – including compliance with Fit for 55 – and enables a higher share of renewables in the energy mix.

In short: lower costs, higher reliability, compliance with EU regulations, and – importantly – the ability to offer added-value services to heat customers who want to actively manage their comfort and reduce heating expenses.

The decision-making process for launching a heating network digitalization project

Below are the key stages of the decision-making process which – if conducted properly – lead to the launch of a district heating network digitalization project.
A Sankey diagram illustrates the dependencies between each stage and their impact on the overall implementation outcome.

1. Preliminary audit – analysis of operating costs

The preliminary audit is the first and critical step toward digitalization and achieving the intended goals. It involves a comprehensive assessment of the technical condition of the heating infrastructure – pipelines, substations, heat sources, and control systems.

The audit also includes financial data analysis – failures, maintenance costs, and energy expenses. Its goal is to identify business and technical areas with the highest optimization potential achievable only through a digitalized network.

The audit should result in a report containing recommendations, a risk map, and an opportunity matrix.

Audit scope:

• Assessment of infrastructure condition.
• Analysis of operating and failure costs.
• Benchmarking against market standards.
• Review of available telemetry and GIS data.
• Inventory of IT tools and functionalities.

The audit results provide decision-makers with insights into current operational efficiency and indicate whether digitalization can reduce costs and improve performance.

It should cover several years of data to capture seasonality and trends and include industry comparisons.

Audit conclusions may point to modernization needs or management strategy changes.
Cost data serve as a foundation for ROI evaluation of future investments – without this, rational digitalization decisions are impossible.

2. Defining strategic digitalization goals

After analyzing the audit results, strategic goals must be clearly defined.
These may include:

• Reducing heat losses.
• Increasing energy efficiency.
• Improving customer service quality.
• Integrating renewable energy sources.
• Reducing network failure rates.
• Engaging consumers in reducing heating costs.

Goals should be measurable, realistic, and aligned with the company’s long-term strategy and stakeholder expectations – both customers and regulators.

Clear goal definitions allow for selecting suitable technologies and implementation methods.

Key questions for the project team to ask stakeholders:

• Are operational savings or network expansion the priority – or both?
• What are the expectations of customers and regulators?
• What are the company’s financial and technological capabilities?

The answers are essential for determining the project’s scope, approach, and schedule.

3. Technical infrastructure assessment

This stage determines the network’s current condition, covering pipelines, substations, heat sources, and control systems, with the goal of identifying elements needing modernization or replacement.

The assessment should be supported by telemetry data and field inspections, considering the age of infrastructure and compliance with standards.

The results of this assessment will indicate which areas are most prone to failures and will allow investment actions to be prioritized.

The resulting report should include:

• A risk map.
• Compliance evaluation.
• Modernization recommendations.

The technical data prepared in this way are essential for selecting the digitalization technologies and inform decisions about the scope of work and the implementation timeline.

Without such an analysis, it is difficult to determine the actual modernization needs, estimate the target project budget, and secure the funds for its execution.

This is a crucial step to ensure the project’s success and, ultimately, to achieve a high level of network safety and reliability.

4. Setting priorities: savings or expansion

The next important step is to set priorities – this is the point where stakeholders must decide whether to focus on modernizing the existing district heating infrastructure or expanding the network.
This decision depends on the results of previous cost analyses, technical evaluations, and compliance reviews.

If the network is in good condition but operating costs are high, the focus should be on cost savings – such as reducing energy purchase and/or production expenses, integrating renewable energy sources (which provide cheaper energy), and diversifying energy supply based on current prices and weather forecasts.

If, on the other hand, there is demand for new connections in areas where the network is not ready to supply new buildings (such as houses, housing estates, or shopping centers), network expansion will be necessary.

Priorities should align with the company’s strategy, stakeholder expectations, urban development plans, and financial capabilities.
This choice directly influences the selection of technologies, the implementation schedule, and defines the key performance indicators (KPIs) that will measure project success.

Hybrid approach – the best of both worlds

The hybrid approach model combines the benefits of operational optimization with infrastructure expansion. It is especially recommended for companies that want to simultaneously improve the efficiency of the existing network and prepare for future market challenges.

Stage 1: implement telemetry, analytics, and control solutions that reduce heat losses, optimize energy use, and enable failure prediction – delivering quick savings.

Stage 2: expand the network – both geographically and technologically – by installing hybrid substations, intelligent controllers, integrating renewable energy sources (RES), and deploying real-time, AI-supported data analytics systems.

Thanks to this, dispatchers gain online visibility into the state of the network – on GIS maps and through Digital Twins of the most critical components.

The hybrid approach enables flexible adaptation to market and regulatory changes, as well as gradual innovation without the risk of destabilizing the company’s operations.

5. Stakeholder engagement – a condition for project success

Stakeholder engagement is an essential condition for the success of any digitalization project. All groups that influence the project or will benefit from it should be identified:

• management,
• the technical department,
• network operators,
• end customers,
• technology partners.

It is worthwhile to conduct informational workshops and consultations to understand the needs and concerns of each group. Transparent communication and jointly developed goals increase project acceptance and minimize the risk of resistance. Stakeholders should be actively involved in successive implementation stages.

6. Selecting technologies: IoT, SCADA, Digital Twin, Big Data & AI

Technology selection is the stage where the tools necessary to achieve the digitalization goals are defined.
The most commonly used solutions include:

• Modern SCADA systems,
• IoT platforms for communicating with network infrastructure (data collection and sending control commands),
• IoT sensors for measuring key network operating parameters (temperature, flows, pressure, heat consumption),
• Digital Twins of key network devices to monitor their operation and anticipate potential failures and/or optimize their control,
• Big Data and AI-class solutions to analyze network data for implementing predictive maintenance, anticipating issues/failures, and supporting dispatchers in optimal network control.

The choice of technologies should depend on the specifics of the network and the project’s priorities.
Solutions must be compatible with the existing infrastructure (unless it is obsolete and needs replacement) and adapted to modern communication methods (IoT) – a fundamental requirement that enables integration, among other things, with billing and Customer Service systems, as well as solutions for Heat Comfort Management on the consumer side.

Because technology selection directly affects implementation costs and effectiveness, it should be preceded by market analysis and consultations with vendors, as well as a sensible approach to adjusting your own requirements – even if some vendors are unable to meet them – and these requirements are critical to your project’s success – do not abandon them unless the target KPIs can be achieved in another way.

Selecting the right solutions increases the chances of project success and ultimately helps meet regulatory requirements such as Fit for 55.

7. Pilot implementation – a practical test of the concept

A pilot implementation makes it possible to test the adopted assumptions in controlled yet real conditions.

Pilot stages:

• Selection of a test area – e.g., a particular district or neighborhood representing the most complex parts of the network,
• installation of devices and system integration,
• KPI monitoring and results analysis.

The purpose of the pilot is to verify how the technologies work in practice and to gather experience that will enable smooth, full-scale implementation.
If, at this stage, it turns out that the concept does not work, you should return to the previous step and change it.
If the pilot implementation is carried out within the public procurement (PZP) process and the Pilot fails – proceed in accordance with the signed Agreement, which should govern such a situation.

8. Project implementation – executing the strategy

The implementation stage is the moment of transition from planning to action. It includes:

• replacement/installation of devices,
• system integration,
• delivery of data models and their analytics layer,
• ensuring data presentation,
• functional and integration testing,
• personnel training.

Real implementation requires close cooperation between technical, IT, and operations teams – both on the maintenance and operations sides.
At this stage, stakeholder support, a clear schedule, a budget, and coordination of activities are crucial.
Implementation must be documented and monitored with particular emphasis on data security and continuity of network operations.

Example implementation schedule:

9. Monitoring results and KPI analysis

The final stage is monitoring the effects of the implementation and analyzing key performance indicators (KPIs).
The purpose of these activities is to assess whether the project delivers the expected results. Monitoring should be continuous and carried out using telemetry systems.
KPI analysis makes it possible to identify areas requiring further optimization and to report results to management and stakeholders.
Monitoring data can be used for continuous system improvement.

The analysis should cover both technical and financial aspects. KPIs should be aligned with the project’s strategic goals – their monitoring increases transparency, control, and the project’s adaptability over time.

This is the stage that closes the digitalization cycle, while at the same time opening the way for its further development.

The role of historical documentation and data in heating network digitalization

Heating companies often have vast amounts of historical documentation related to network operations – operational reports, service orders, defect lists, or repair protocols. Digitizing this data using OCR (Optical Character Recognition) makes it possible to create a central analytical database that combines historical data with current telemetry measurements.

Thanks to this approach, it becomes possible to analyze these data in the same way as network data – using Big Data solutions with AI support:

• searching the content of digitized documents by keywords,
• analyzing the frequency of failures,
• assessing the effectiveness of maintenance actions,
• correlating historical data with current telemetry data,
• building predictive models based on a long-term failure history.

Such a knowledge base significantly increases the possibilities for data analysis (including historical data from before the company’s digitalization project), enabling a better understanding of processes occurring in the network and more effective planning of preventive and investment activities.

Checklist for digitizing historical documents

The process of digitizing historical documents should follow clearly defined steps. The checklist below helps maintain order, data quality, and consistency of the entire repository.

1. Inventory of available paper and digital documents.
2. Assessment of document quality and selection of an appropriate digitization method (scanning, OCR).
3. Text recognition (OCR) and conversion to an editable format (e.g., DOCX, TXT).
4. Validation of the recognized text’s accuracy.
5. Standardization of formats and metadata to unify the data structure.
6. Import of data into the target analytical system database.
7. Integration with analytical and AI systems that will enable subsequent data processing.
8. Maintenance and updates of the repository – ensuring its continuous currency and quality.

Documents worth digitizing and their analytical significance

It is advisable to first digitize documents that contain important operational and strategic information. Converting and storing them in a database enables later analyses, reporting, and building predictive models.

The most important documents to digitize:

• operational reports – data on network operation, technical parameters, heating seasons,
• service and repair orders – types of failures, response times, repair costs,
• reported defect lists – location and frequency of issues,
• acceptance and technical inspection protocols – the technical condition of infrastructure,
• invoices and cost documents – costs of energy, fuels, materials,
• modernization and investment documentation – project descriptions, schedules, ROI.

Analyzing these documents enables:

• identification of areas requiring modernization,
• optimization of operating costs,
• investment planning and evaluation of their effectiveness,
• building predictive models and supporting strategic decisions.

Data integration and the role of artificial intelligence in using documents

Digitized documents should be stored in a central analytical system database, enabling quick access to content, metadata, and change history.

How to use such digitized documents? Especially valuable are AI-based solutions that allow the user – e.g., a dispatcher, operator, or engineer – to communicate with the system in natural language, both textually and by voice. The user can ask questions about the documentation content, and the system searches for answers in its assigned datasets and technical documents.

We have implemented this type of solution on our Smart RDM analytical platform, which enables:

• assigning documents to specific user groups who, within a secure space, can search them – without the risk of data leakage or uncontrolled Internet access (so-called hallucinations are minimized),
• searching content based on questions asked in natural language – both text and voice,
• integration with process data – the user can not only search documents but also ask questions about data from process databases, for example about statistics, summaries, or rankings.

As a result, Smart RDM transforms traditional technological documentation into an active source of knowledge, supporting operational decisions and significantly accelerating daily work.

Data should be indexed by document types, dates, locations, types of failures, and maintenance actions, or in any other way agreed upon at the analysis stage. Integration with telemetry systems makes it possible to combine historical data with current measurements, which forms the basis for predictive models and comparative analyses.

Goals of heating network digitalization and key performance indicators (KPIs)

The effectiveness of heating network digitalization can be measured using clearly defined KPIs (Key Performance Indicators). They make it possible to assess both the technical and financial aspects of project execution.

Examples of successful implementations in Poland and Europe

Polish district heating companies increasingly show that digital transformation is not theory but real results. In Warsaw, Veolia, together with ConnectPoint, implemented the Smart District Heating Network 2.0 project – one of the most advanced in Europe. The system already includes more than 6,000 controllers, and its implementation has reduced CO₂ emissions by 14,500 tons per year – you can read more about the detailed assumptions and results of this project in our case study. Parallel programs to improve efficiency and manage customers’ thermal comfort demonstrate that digitalization can go hand in hand with care for the end user.

In Puławy, modernization of substations and network telemetry made it possible to integrate RES installations, increasing the city’s energy independence. In Bełchatów, a remote control system and IT infrastructure modernization were implemented, significantly improving response times to network events. Kwidzyn, in turn, focused on automating heat meter readings – enabling real-time monitoring of heat consumption and more accurate billing for consumers.

At the European level, the RELaTED project is noteworthy; it promotes low-temperature district heating networks and the use of heat pumps, waste heat recovery, and bidirectional substations. This direction sets a new standard for modern, sustainable district heating systems.

Summary: from data to decision-making – how digitalization changes district heating

Digitalization of district heating networks is no longer a project of the future but a necessity and an opportunity for lasting competitive advantage. Thanks to the integration of telemetry data, real-time analytics, Digital Twins, and artificial intelligence, heating companies gain full visibility into the state of the infrastructure – from the source to the consumer.

A properly planned digitalization process – from the audit, through defining strategic goals and choosing technologies, to implementation and KPI analysis – makes it possible to genuinely reduce costs, increase operational efficiency, and improve service quality.
At the same time, it enables better use of historical data, which – once digitized – become the foundation for predictive models, ESG reporting, and intelligent modernization planning.
Today, digitalization is not only a tool for process optimization – it is a strategic element of the energy transition that supports the implementation of EU climate goals and the development of a modern heat economy.

Do you want to digitalize your heating network but don’t know where to start?

Start with an audit of infrastructure and data, move on to designing the telemetry and analytics architecture, and then implement SCADA, IoT, Digital Twin, and AI systems.
ConnectPoint has supported heating companies for years in end-to-end digitalization – from data analysis and modeling, through system integration, to building modern analytics platforms in the cloud and on-premises.

With the experience of the ConnectPoint team and implementations in Poland and abroad, we help companies move from the vision of digitalization to measurable business results.

👉 Contact us if you want to learn how to carry out the digitalization of your network step by step – from the audit to KPI analysis. Together, we will build an intelligent heating network or deliver your other projects!