The future of District Heating and Cooling: Mastering heat propagation to seize flexibility opportunities
District Heating and Cooling (DHC) companies are facing increasing complexity, from managing heat supply and navigating volatile electricity markets to supporting power grid stability. Yet, within this complexity lies a powerful opportunity: flexibility. By unlocking the potential of their networks, companies can undertake the next step in realising the full potential of sector-coupling.
This article outlines how embracing flexibility is key to transforming challenges into competitive advantages while building a more resilient and sustainable future.
DHC operators: Key enablers of the smart energy transition
As Europe transitions toward a more sustainable and resilient energy infrastructure, District Heating and Cooling (DHC) companies play a critical double role: decarbonising heating and cooling production for millions of inhabitants and balancing national power grids through electricity production and consumption.
Given that heating accounts for nearly half of the world’s total energy use, this dual mandate positions DHC operators at the heart of the energy transformation, requiring strategic leadership to navigate growing complexities.
One example of a company that operates well in this complex landscape is Veolia, a European leader in flexible power management. It generates 2 GW of flexible power across 10,000 industrial sites, an output comparable to the power consumption of two million people. With such an expansive asset base, companies can, for example, respond swiftly to price fluctuations on day-ahead and intraday markets while supporting grid stability through ancillary services as more intermittent renewable sources are integrated.
Unlocking new flexibility with district heating grids
Additionally, incorporating district heating grids into the equation could unlock even greater flexibility. Even if that involves a new layer of complexity given that maintaining reliable and predictable heat delivery to citizens remains a crucial obligation.
The International Energy Agency believes that unlocking this potential is essential. This is especially true since the global need for flexible assets is expected to grow tenfold by 2030 driven by Europe's rapid expansion of over 500GW of PV and wind energy.
A major component in the flexible portfolios of these key players are currently the large co-generation plants they have already been operating for decades. Combined Heat and Power (CHP) plants are particularly efficient, producing electricity for the grid while simultaneously delivering heat to district heating networks. For example, in the city of Łódź in Poland, power plants have a combined capacity of 400 MWe for power production and 1600 MWth for heat production, supplying around 400,000 residents with heat.
Building flexibility with a diversified energy mix
However, the role of these traditional co-generation plants is evolving. DHC companies diversify their supply portfolios to enhance operational flexibility and operate based on increasingly volatile electricity markets.
Also, many are incorporating (decentralised) renewable heat sources, such as heat pumps and e-boilers to further expand their flexibility potential. While these assets offer great value, unlocking their flexibility is a challenge to fully achieve their benefits.
In parallel, companies are adding thermal energy storage capacities and e-boilers to create more flexibility. This transition is complex, requiring operators to extract maximum value from existing systems while adapting to new, distributed energy setups.
For example, the Finnish energy company Helen is replacing coal-based heat supply with large-scale heat pumps at newly integrated locations within their network, while simultaneously adding storage systems and e-boilers to bolster flexible capacity.
Similarly, Envafors in Denmark is integrating electricity-consuming heat pumps and thermal energy storage capacity in their systems next to their co-generation assets. With the added responsibility of purchasing electricity at favourable times, making the right operational decisions to ensure profitability has become increasingly complex.
Using the right asset at the right time is a challenge
Effectively utilising a co-generation asset, the most common asset for DH companies to produce both electricity and heat, is an opportunity and risk at the same time.
It is an opportunity since heat can be produced at a more affordable price, for instance compared to a heat-only boiler. But it is also a risk as volatile power prices on the day-ahead market make it difficult to precisely understand the expected profits.
Another risk is that the amount of electricity a co-generation plant can produce is heavily influenced by the heat that must be generated to meet citizens’ demand. This is why the heat load can also be a limiting factor for the amount of electricity a co-generation owner needs to produce. Also, if the heat load forecasts turn out to be incorrect, the resulting electricity quantities must be corrected by trading based on hard-to-predict intraday prices.
DHC operators, particularly those managing decarbonised systems, often rely on multiple assets. Next to co-generation, they use heat pumps, e-boilers, and energy storage to run their operations. When electricity prices are high, co-generation assets are prioritised over heat pumps and e-boilers. And the other way around, low prices favour these electrical-consuming assets, saving the fuel that combustion engines would burn.
Some DHC operators also commit in electricity capacity markets, securing valuable revenue streams. However, when the electricity grid operator activates their co-generation commitment, the DHC operator must act within minutes to ensure the corresponding heat production is efficiently managed, either by utilising storage or reducing output from other heat sources.
An operator of a DHC network needs to make difficult hourly decisions to balance heat load requirements, electricity prices, and asset efficiency. Ensuring the right asset is used at the right time is critical to maintaining both economic performance and reliable heating and cooling supply.
Beyond selecting which assets to use, companies must ensure their network can support this strategy. Decentralised sources, thermal storage, and the diverse demand profiles add complexity, making it essential for production schedules to be not only profitable, but also hydraulically validated, feasible and reliable.
A deep understanding of real-time network conditions, capacity constraints, and evolving market dynamics has shifted from a ‘nice-to-have’ to an absolute necessity.
Complexity amplified: Heat propagation meets electricity volatility
Understanding heat propagation
Scheduling heating supply involves much more than simply knowing the total demand. It requires precise insights into where and when energy is needed. Heat demand is distributed across the network, with each asset location responsible for supplying its specific share. Unlike electricity that balances almost instantly, heat transport involves delays ranging from a few minutes (in smaller towns) to several hours or more (in large cities), as heat usually travels at 1-2 m/s through pipes.
In larger and more complex networks, especially ones where operators also produce power and act as a balancing partner, such time lags significantly increase the complexity of decision-making.
The graph below shows how a ‘heat wave’ propagates through a network. The temperature is the highest at the source and drops slightly lower for each user located at some distance. It also takes time before an increase at the source is observable at the user’s location, as illustrated on the timescale of the x-axis.
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This delay, also known as heat propagation, can only be fully understood through a physics-based perspective. Flow and pressure conditions in both forward and return lines, as well as settings of valves, mixing points, and heat losses along the way, all influence the heat flow that ultimately reaches the end customer.
Heat propagation introduces inherent time lags between production and consumption. As a result, choosing the right asset at the right time while considering fluctuating energy prices is a highly intricate task: you need to plan in advance.
In addition to heat propagation, the pipe sizes can present a capacity limit for the amount of heat that can be transported. In traditional systems with just a few major feed-in points, the network was designed to transport heat in one direction. In new-generation networks, decentralised sources distributed across the network can completely change the hydraulic dynamics.
Currently, many heating companies rely on a few pressure sensors to decide when to activate a (peak) source. But what if the sensor is no longer positioned at the most critical point after adding new neighbourhoods to the network?
This is just one among many questions that may arise:
Which users are drawing enough flow to cause a pressure drop, and by how much should the temperature be raised to correct it?
Can the central source handle this adjustment, or is a peak boiler needed?
And critically, is the production schedule actually feasible within the network?
Or will any hydraulic bottlenecks occur and hinder succeeding in the preferred heat distribution at all?
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The image above demonstrates the challenge of understanding which heat source supplies which area in real-time, with each colour representing a specific source. In this example, the operator manages more than 20 different heat supply points. Making operational decisions solely on a handful of pressure sensors is already a complex task, and it does not immediately translate into the detailed insights of the best possible decisions.
Meanwhile, DHC operators must also factor in fluctuating electricity prices to determine which heat sources are most advantageous at any given moment.
Seizing electricity market volatility
Next to thermohydraulic complexities, navigating electricity markets presents DHC operators with a unique set of challenges, as each market operates with distinct price dynamics. Below is an example of a typical day on the German electricity market during summer.
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Source:
Energy-Charts , Fraunhofer Institute for Solar Energy Systems ISE, "Electricity production and spot prices in Germany in week 27 2023."
Strom-Markt-Daten , Bundesnetzagentur, Electricity generation, Data for 17 June 2023.
The lines on the graph illustrate typical opportunities and risks that a DHC operator should consider when planning power production and consumption.
The day-ahead market: This market is familiar to most European DHC operators. While prices vary throughout the day, often by a factor of 2–3 or more, e-production and consumption quantities are balanced a day in advance, giving operators a clearer expectation of what lies ahead.
The intraday market: Represented by the light blue line, this market is more volatile than the day-ahead market. DHC operators using heat pumps or e-boilers will be familiar with this market. Trading decisions can be made throughout the day, with transactions occurring in 60-, 30-, or even 15-minute intervals. Although this offers many opportunities to sell electricity at high prices, it also carries a higher risk of underselling electricity generated or overpaying for electricity consumed as fuel.
The automatic frequency restoration reserve market: The red and purple lines are a typical example of a market used by a country’s transmission system operator (TSO) to balance the grid on a very short-term basis. Participants can submit bids to adjust e-generation within the next period at a given price (e.g., the offer is valid for the next 25 minutes). If the e-grid frequency becomes unstable, DHC operators may be required to adjust generation within a 5-minute warning. Prices in these markets can be very high, encouraging operators to increase electricity consumption (and get paid for it) or reduce production while still earning revenue without using additional fuel. While most CHPs can’t respond quickly enough, e-boilers and heat pumps enable participation in these markets.
Next to that, there are other ancillary markets offering similar revenue opportunities to those shown by the red and purple lines (AFRR) above. These markets are designed to provide grid stability on a very short-term basis (within 15 minutes) and may be implemented differently across countries, such as in capacity, reserve, or frequency markets.
Navigating these markets requires both operational expertise and strategic coordination, making the daily life of a DHC operator far from easy.
While traditional CHPs require hours to ramp up or down, e-boilers and heat pumps can adjust to full capacity within minutes. This capability positions DHC operators as key providers of flexibility to the electricity grid, enabling them to respond effectively to intraday price signals and participate in ancillary markets.
Altogether, the interplay of volatile electricity prices, transition of assets, and the described intricate thermohydraulic dynamics and heat propagation creates a significantly complex challenge for DHC operators seeking to optimise heat and power production schedules. But despite these difficulties, the goal remains clear: delivering reliable heat to citizens while staying competitive and cost-effective.
Future-proofing operations with flexibility as an opportunity instead of a risk
To manage operational complexity and transform it into a strategic advantage, DHC companies must leverage smart digital solutions.
These solutions create value from the immense amount of data that is often already available. They transform data into actionable insights, support decision-making, and are the basis to automate processes and choices that are too complex for human analysis alone. A smart optimisation layer offers a new level of system understanding and turns flexibility into a powerful asset.
Digital strategy is not just about addressing today’s challenges but also building a future-ready foundation. Most DHC operators have already taken steps toward this goal, using smart daily calculations to guide their heat and power production.
A simple check is asking: How much value does your current digital landscape create from every new hourly sensor reading? If any data signals from your DCS, IoT devices, or smart heat meters still aren’t reaching a smart, digital layer, you’re leaving value on the table.
As electricity markets are expected to grow more volatile in the coming decades, and new innovations such as complex renewable assets and demand-side control are introduced across the DHC systems, deploying a smart optimisation layer becomes essential.
With the right digital strategies, DHC companies can seize flexibility to remain competitive and profitable while always ensuring reliable heat production. Key steps to achieving this include:
1. Connecting data across systems
Integrate real-time signals from e-markets, SCADA/DCS systems, network sensors, and smart meters to create a unified and overarching view of the actual system conditions and flexibility.
2. Forecasting heat demand with network dynamics included
Go beyond basic demand predictions toward more detailed and accurate forecasting. Anticipate energy needs for each user and track how heat moves through each pipe in the network. Ensure that flow limits, pressure drops, and thermal stress level are not exceeded to prevent bottlenecks. This approach reveals exactly where and when energy is needed, ensuring efficient distribution strategies.
3. Maximising the flexibility of storage
Unlock the full potential of thermal storage to shift production over time, enhancing flexibility and balancing loads. Thermal storage offers a cost-effective solution, being over 100 times cheaper than electricity storage. A heating network can also serve as ‘one big accumulator,’ storing heat directly within its pipes. Learn more about leveraging storage flexibility here: Maximising flexibility with thermal storages without operational risk
4. Understanding the real efficiency of your assets
Base decisions on real-world performance rather than outdated manufacturer specifications. Over time, assets may deteriorate or change, affecting efficiency. A data-driven understanding of fuel use, temperature sensitivities, and power-to-heat ratios ensures operational schedules are both efficient and feasible.
Building on these principles, Gradyent has supported several DHC companies in implementing Digital Twins and establishing a smart optimisation layer, enabling them to optimise their end-to-end systems while maximising flexibility potential.
Unlocking flexibility with a Digital Twin
Central to this transformation is Gradyent’s real-time Digital Twin Platform, which provides a live virtual model of the entire system. Operators can simulate “what-if” scenarios, examining how adjustments to temperature or asset dispatch impacts system dynamics and profitability.
By combining insights into past, present, and future hours in parallel, the platform empowers teams to make informed decisions that enhance both efficiency and sustainability.
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Real-time insights are the cornerstone for pushing the boundaries of what’s possible within system limits.
By validating actions through a virtual cockpit, operators can ensure system stability remains uncompromised while unlocking new opportunities to monetise flexibility, such as participating in electricity trading or leveraging ancillary services. This adaptability strengthens resilience in dynamic market conditions.
This comprehensive approach has enabled several clients to tackle the complexities of their heating systems while unlocking significant asset flexibility.
For instance, Gradyent found that real-time dynamic price calculations and optimisation on a minute-to-minute basis could increase the profitability of existing CHP plants by more than 4%, while reducing CO2 emissions with more than 3% in winter months, based on a case involving diverse assets, locations, and fuel choices. This demonstrates that flexibility goes hand-in-hand with profitability.
Are you interested in learning more about how the Digital Twin works? Get in touch with us to schedule a demo.