Dynamic Regulation and Renewable Integration for Low-Carbon District Heating Networks

Abstract

Integration of renewable energy sources into existing residential and communal district heating systems requires technical adjustments and corrections. Measures aimed at reducing heat consumption at the points of delivery have a similar impact. This study aims, through simplified partial models (in heating mode), to present the relationships between these modifications and their potential effects on operational problems and deficiencies. The main parameters assessed in the design and correction of systems are temperature differentials, derived flow rates, pumping work, and control methods. Within the chain of heat source–primary distribution–secondary distribution–consumers, the analysis focuses on secondary circuits with consumers. A simplified multi-building network model was used to compare static and dynamic control strategies under temperature regimes of 70/50 °C, 60/40 °C, and 40/30 °C. The results show that dynamic control based on variable-frequency pumps, weather-compensated supply regulation, and optimized temperature differences between supply and return lines (ΔT) reduces pumping energy by 30–40% and increases heat delivery efficiency by up to 10%. A significant reduction in CO₂ emissions is also observed due to decreased pumping work, reduced heat losses in the distribution network, and the integration of renewable energy sources. The savings depend on the type and extent of RES utilization. The implementation of dynamic control in these systems significantly improves exergy efficiency, operational stability, and the potential for low-temperature operation, thus providing a practical framework for the modernization of district heating networks.

1. Introduction

Heating accounts for almost half of Europe’s final energy demand, making the decarbonization of thermal supply a key priority under the EU Green Deal and the Paris Agreement [1,2,3,4]. The building sector plays a crucial role in the energy transition, as most heat consumption is associated with heating residential and public buildings. Therefore, reducing the carbon footprint and increasing the energy efficiency of buildings require the modernization of heat supply systems at the district and city levels. District heating systems (DHSs) play a central role in this transition, as they deliver energy to households and public buildings [5,6]. The typical configuration of a DHS is shown in Figure 1. However, conventional DHSs were typically designed for static operation, with oversized flows, with temperature regimes controlled based on the return water temperature to the heat source and throttling control at the points of consumption. These legacy designs often lead to excessive pump electricity use, low exergy efficiency, and significant barriers to the integration of renewable energy sources (RES) [7,8,9]. This leads to increased losses, higher operating costs, and a larger carbon footprint of urban district heating networks.

The concept of 4th generation district heating (4GDH) promotes low-temperature operation, dynamic regulation, and decentralized renewable integration [5,10,11]. Within 4th generation district heating, advanced technologies such as variable-frequency-drive (VFD) pumps, distributed variable-speed pumps (DVSP), and model predictive control (MPC) play a significant role. These solutions have already demonstrated the ability to reduce pumping energy consumption by 25–40% and to improve the supply–return temperature difference (ΔT), thereby supporting more efficient operation of building systems [12,13,14]. Similarly, hydraulic optimization strategies such as reverse-return layouts, automatic balancing valves, and thermal buffers have been shown to improve system stability and enable deeper renewable penetration [15,16,17]. This enables deeper integration of renewable energy sources and improves overall energy efficiency [12,13,14]. These technical measures are crucial not only for the modernization of existing networks but also for achieving the goals of climate neutrality and a green economy.

Despite rapid technological progress, significant gaps remain in both research and practice. First, many networks in Central and Eastern European (CEE) countries still operate with static regulation, while modernized, insulated buildings often cause hydraulic imbalances that prevent low-temperature operation [18]. Second, although dynamic control and hydraulic optimization have been studied separately, few studies have examined their combined impact on energy savings, improved exergy efficiency, and CO₂ reduction in real networks [13,14,18]. Third, the implementation of 4GDH is still constrained by fragmented policy and technical frameworks, which hinder the large-scale adoption of innovative low-carbon solutions [19].

The aim of this paper is therefore threefold:

(i)

To analyze the limitations of static regulation and demonstrate the benefits of dynamic control in heating networks;

(ii)

To evaluate the combined role of hydraulic optimization and advanced control in improving efficiency, performance, and emission reduction;

(iii)

To discuss the sustainability and policy implications of these measures in the context of Sustainable Development Goal 7 (Affordable and Clean Energy) and Goal 13 (Climate Action) [20].

By addressing these objectives, the paper contributes to expanding knowledge on the modernization of district heating systems in Central and Eastern Europe and offers a framework for their integration into energy-efficient and sustainable buildings. The study also bridges the technical and policy dimensions of the transition toward low-carbon thermal systems and reinforces their connection to the goals of the green transition in construction and renewable energy.

1.1. Overview of Knowledge

District heating systems have traditionally relied on static control methods, which ensure hydraulic balancing and flow regulation but cannot optimally adapt to fluctuating outdoor conditions or variable building demand. This inflexibility often results in overheating, noise, and excessive pumping energy, particularly in multi-building networks with mixed insulation levels [21,22,23]. The main parameters of the analyzed buildings are summarized in

Table 1. Characteristics of the buildings: heating-water temperature parameters.

OBJECTS		PRIMARY		SECONDARY		OBJECT		HYDRAULIC	EQUITHERMAL	HEATING CHARACTERISTICS AND OBJECT REGULATIONS
Labeling	Insultation	T1 °C	T2 °C	T1 °C	T2 °C	T1 °C	T2 °C	OVERREGULATION	REGULATION
A				70	50	70	50			MOST UNFAVORABLE object determining parameters HTS
B	Yes			70	40	70	40	Yes		HYDRAULIC REGULATION BY FLOW REDUCTION
C	Yes			70	50	60	40		Yes	TEMPERATURE REDUCTION WITH EQUITERMIC REGULATIONS
D		120	60			70	50		Yes	OWN EXCHANGER STATION own parameters

. Static control therefore represents a key bottleneck for energy efficiency and renewable integration in centralized heating systems.

1.1.1. Static Versus Dynamic Regulation

Static regulation is based on fixed kv-values, manual balancing valves, and constant-speed pumps. While low-cost and reliable under narrow design conditions, it fails under off-design situations. Studies show that static systems can waste 20–30% of supplied heat due to poor valve authority and oversupply [22,23]. In contrast, dynamic control employs differential-pressure regulators, variable-frequency-drive pumps, and weather-compensated supply adjustments. Dynamic systems adapt to real-time demand, enabling 25–38% pumping energy savings and more stable ΔT conditions. Dynamic regulation is therefore recognized as a core element of 4th generation district heating [12,13,14].

1.1.2. Advanced Control Strategies: MPC and DVSP

Recent progress in model predictive control (MPC) and distributed variable-speed pumps (DVSPs) has advanced the flexibility of DHS. MPC frameworks optimize supply temperatures and pressures based on weather forecasts and system states, achieving up to 12% lower energy use compared to proportional-integral regulators [24,25,26,27]. DVSPs replace throttling valves at the building level, enabling each branch to modulate flow independently, which has been shown to reduce pump energy by over 30% in complex multi-branch networks [28]. These strategies improve both comfort and system-wide efficiency while creating favorable conditions for low-temperature operation.

1.1.3. Hydraulic Optimization

Hydraulic design strongly influences the operational efficiency of DHS. Automatic balancing valves and properly dimensioned control valves have been demonstrated to improve flow uniformity and reduce energy losses [19]. In retrofitted buildings, where insulation lowers heat demand, imbalances often emerge unless networks are re-optimized [21,29]. Maintaining a large ΔT between supply and return is critical not only for reducing pump energy but also for improving exergy performance and enabling the operation of condensing boilers and heat pumps [19,30]. Case studies confirm efficiency gains of 7–17% and reductions in peak fuel usage up to 30% through active ΔT management [30,31,32].

1.1.4. Thermal Separation and Storage

While they stabilize flow, internal mixing can degrade temperature delivery, especially in condensing boilers or heat pump applications [15]. An increasingly favored alternative is the use of buffer tanks, which provide thermal inertia and minimize unwanted mixing. Simulation studies suggest that buffer tanks enhance operational stability in multi-source networks, absorb fluctuations, and improve integration of intermittent renewables. These thermal-storage solutions are becoming essential for 4GDH [16,17].

1.1.5. Integration of Renewable Energy Sources

The decarbonization potential of DHS depends on the integration of low-temperature renewable sources such as solar thermal, geothermal, and ambient heat via heat pumps. When coupled with dynamic control and optimized ΔT, RES integration has achieved lifecycle CO₂ reductions of up to 77% [17,19]. Cold and ultra-low-temperature district heating concepts are emerging, particularly in Northern and Western Europe, but their widespread implementation requires coordinated technical and policy support [10,33,34,35].

2. Materials and Methods

The methodological framework of this study combines the thermal–hydraulic characterization of a representative heating system with scenario-based simulations of static and dynamic regulation. The approach follows established engineering standards [36,37,38,39] and recent optimization studies on low-temperature and renewable-integrated heating systems [10,11,29,40].

2.1. Case Study System

The analysis was conducted on a centralized heat supply system (Slovakia—Košice) typical for the residential–communal sector in Central and Eastern Europe. The primary circuit is supplied by a central boiler plant (natural gas, coal, with a connected biomass source and a municipal waste incineration plant) operating at supply temperatures up to 120 °C. The primary distribution network has a total length of approximately 200 km. Through heat transfer stations, energy is exchanged to secondary networks, which commonly operate in a 70/50 °C regime.

The studied secondary network supplies various buildings, from which four typical ones were selected with heterogeneous thermal characteristics. Uninsulated buildings (A and D) operate at a 70/50 °C regime, while retrofitted buildings (B and C) have lower heat demand. These insulated buildings adopt either quantitative control (flow reduction, Building B) or qualitative control (temperature reduction, Building C). Such a configuration reflects real urban networks, where the most demanding building (A) typically dictates HTS setpoints [12,13]. This mixed-demand system provides an appropriate basis for comparing static and dynamic regulation strategies.

2.2. Parameters and Indicators

System performance was assessed using the fundamental thermal power relation:

Q = m⋅c⋅ΔT

(1)

where Q is thermal output (W), m is the mass flow rate of water (kg/s), c its specific heat capacity (4.18 kJ/kg·K), and ΔT the supply–return temperature differential (K). The relation between outdoor temperature and supply temperature is illustrated in Figure 2. The simulations were carried out using commercial software for the calculation of heating system hydraulics and water distribution networks. Many parts were solved using our own computational models. In standard design calculations, only one characteristic operating state is typically considered. In our calculations, entire operating ranges of the systems are taken into account—from zero load to maximum utilization. The graphs present the results of simulations and measurements, as well as trends and areas where systems may already exhibit operational problems. These graphs are intended to support decision-making regarding which system to choose and to illustrate its possibilities, advantages, and limitations. Each described system represents a separate mathematical problem. In practice, these systems are often combined and mutually influence each other. A detailed description of the simulation models would go beyond the scope of this publication.

Three operating regimes were investigated:

• 70/50 °C (high-temperature—non-insulated buildings)—representative of legacy heating systems with elevated distribution losses.
• 65/55 °C (transitional—isolated buildings)—extending condensing-boiler efficiency to outdoor temperatures of approx. −9 °C [11,19].
• 40/30 °C (low-temperature—newly designed buildings)—optimal for integration of heat pumps and solar thermal systems [10,17].

The evaluation criteria included:

(i)

ΔT stability, as an indicator of hydraulic balance and exergy efficiency;

(ii)

pumping electricity consumption derived from pump and system curves;

(iii)

heat-delivery efficiency as the ratio of useful to supplied heat;

(iv)

CO₂ reduction potential, quantified for renewable integration scenarios.

2.3. Control Strategies

Two types of regulation were examined in this study: static control and dynamic control. Static control is based on fixed kv-values, manual balancing valves, thermostatic radiator valves (TRVs), and constant-speed pumps. Although this approach is inexpensive and simple to apply, it lacks flexibility. Earlier studies show that static regulation may lead to 20–30% heat losses because of poor valve authority and oversupply [22,23]. The behavior of pumps with constant or switchable speeds is illustrated in Figure 3, along with their characteristic performance curves.

The interaction between pump performance and system resistance determines the actual operating point of the network. As shown in Figure 4, system resistance curves vary with pipe diameters and flow rates, which has a direct influence on pressure drops and overall network stability.

Hydraulic optimization further supports the performance of control systems. Reverse return arrangements (Tichelmann) help stabilize flow distribution, ensuring more uniform pressure regulation in distribution networks, as shown in Figure 5. The Tichelmann configuration is particularly suitable for connecting solar panels or cascade heat sources, provided they are connected within a system using a common circulation pump.

The effect of flow variation in a heating circuit on pressure conditions is demonstrated in Figure 6. This example shows a very long distribution line with a circulation pump located at the heat source and a consumer positioned at a considerable distance. For simplification, the consumer is represented by a control valve.

In case “A,” the control valve is fully open, assuming its minimum pressure loss. The main component causing the differential pressure is pipe friction. A high flow rate passes through the circuit, and the pump operates at a low head, as shown in Figure 6a—operating point “A.”

In case “B,” the control valve is extremely throttled, resulting in a minimal flow rate through the pump and, consequently, an increased pump head—operating point “B.” The outcome is wasted pumping energy and high stress on the control valve. In extreme situations, the actuator of the control valve may not be able to regulate the valve properly. The valve and actuator may become damaged during operation. This situation is suitable for the application of dynamic control.

2.4. Simulation Framework

The simulations take into account 30 years of experience in the design and operational optimization of secondary heating networks and buildings following thermal insulation and hydraulic balancing. A simplified thermal–hydraulic model of the secondary network was constructed. Input parameters included building heat loads (30–50 W/m² for insulated and 80–120 W/m² for uninsulated buildings), pipe diameters and roughness values consistent with EN 12828 [36], and climate data for Central Europe (average winter temperature −1.8 °C; ~230 heating days annually). The objective was to highlight potential issues and interrelations in different control systems and thermal demands of buildings. The buildings are generally connected to a common secondary distribution network. The description of the buildings is provided in Figure 1 (buildings A, B, C, and D).

The simulations of the secondary distribution networks were carried out in four steps:

• Steady-state analysis of hydraulic balance under static and dynamic control.
• Parametric variation in ΔT (5–25 K) to evaluate impacts on pump electricity and thermal efficiency.
• Scenario testing across three temperature regimes (70/50 °C, 65/55 °C, 40/30 °C).
• Renewable integration analysis, including heat pumps (COP 3.0–3.5) and solar thermal collectors (15–20% annual coverage), integrated via buffer storage [10,17,41].

By combining these steps, the methodology provides a systematic framework to quantify how advanced regulation and hydraulic optimization influence the energy and environmental performance of DHS. While the model reflects real operational conditions, it remains a simplified representation; limitations related to long-term variability and component-specific behavior are discussed in Section 4.3.

3. Results

3.1. Static Regulation

The baseline analysis under static regulation revealed significant inefficiencies. With constant-speed pumps and fixed kv-values in certain situations, it was unable to adapt to fluctuating demand.

When thermostatic radiator valves modulated, differential pressures increased beyond the optimal control range, forcing valves into throttling regimes. This effect led to unstable flow, valve noise, and localized overheating. The simulations confirmed that pumping electricity was on average 20–25% higher compared with dynamic regulation, while the temperature differential (ΔT) fluctuated between 5–8 K. These findings mirror other studies of poorly balanced networks, which reported excess return temperatures and increased energy consumption of up to 30% [21,22,23]. The pressure and flow maldistribution under static regulation are illustrated in Figure 7. Despite static regulation, the system behaves dynamically due to the influence of thermostatic valves. The authority of other static fittings and pipelines decreases as the flow rate drops. The pump in the system is modeled as operating along a constant performance curve (Figure 9A). During transitional periods, when the outdoor temperature is around 12 °C, and the implemented heat consumption metering on heating radiator, the flow rate can decrease to as low as 50% of the nominal value. This occurs even with properly functioning equithermal control. When the flow rate drops to approximately 85% of the nominal value, the thermostatic valve may enter a noise and discontinuous control zone, indicated by a red arrow on the graph. The system operates correctly only within a narrow range, and excessive throttling results in wasted pumping energy.

Main principles of static regulation:

• Hydraulic balancing of the system

  -

  Are intended to ensure a uniform water flow through all branches and heating elements.

  -

  Balancing valves and presettable radiator valves are used. During the design process, it is necessary to maintain valve authority between 0.3 and 0.7.

$$a={\displaystyle \frac{\mathrm{\Delta }pv}{\mathrm{\Delta }pv+\mathrm{\Delta }ps}}$$

(2)

Δpv = pressure drop across the valve at full flow (fully open valve) (kPa)

Δps = pressure drop of the remaining circuit (other pipes, fittings, heat exchangers, etc.) (kPa)

Too low authority (e.g., a < 0.2): the valve has little influence on the flow → poor control, nonlinear characteristics. Too high authority (a > 0.8): the valve causes a large pressure drop → energy inefficient.

Flow adjustment

• Each heating element requires a specific flow rate according to its thermal load.
• The flow rate is set based on calculations and manufacturer valve tables.

Pipe and pump sizing

• The pipes must be properly dimensioned to avoid excessive pressure losses or noise.
• Pumps should be designed for optimal performance to ensure proper circulation.

Presetting of control components

• Thermostatic valves are adjusted according to the required output of the heating element and the available pressure before the terminal unit.
• Static balancing valves are set to ensure hydraulic balance between branches/risers and to relieve thermostatic valves in their operation.

Advantages of static regulation:

• Simplicity and reliability; it is easy to install and set up, with fewer electronic components that could fail.
• Lower investment costs compared to dynamic or intelligent control systems.
• Stable operation if parameters are properly adjusted and the system operates within a narrow working range.

Disadvantages of static regulation:

• Lack of flexibility; it cannot adapt to significant changes in external conditions.
• Lower energy efficiency; potential occurrence of overheated or underheated zones.
• Requires manual adjustment when conditions change.
• When using a pump without a frequency converter, throttling results in wasted pumping energy.

In practice, static regulation is often combined with or completely replaced by dynamic regulation.

3.2. Dynamic Regulation

Dynamic heating control is a more advanced method of managing heating systems, enabling automatic real-time adjustment of heating output based on current conditions. It ensures higher energy efficiency and comfort compared to static control. Two basic methods of differential pressure regulation can be distinguished: throttling control and pump power control.

3.2.1. Dynamic Control Using Differential Pressure Regulators

The main component of the system that ensures dynamic regulation, as shown in Figure 8, is the differential pressure controller. This fitting is connected between the supply and return pipelines by a capillary tube, through which it senses the differential pressure and maintains it at the set value. When the differential pressure increases, the valve throttles the flow and absorbs the excess pressure (area marked in green). In this way, it relieves the thermostatic valves (area marked in red) and reduces the risk of noise and undesirable sound effects. At the same time, it allows other fittings to operate within their optimal ranges. The valve is very reliable in operation; however, when the differential pressure is excessive, it wastes pumping energy if the pump is not equipped with a frequency converter. In the case shown in Figure 8, the pump operates in a conventional mode according to a constant characteristic curve (Figure 9A). The system can also operate with a pump as shown in Figure 9B (with constant pressure).

This strategy led to a 20–25% reduction in pumping electricity consumption while maintaining ΔT stability within ±1–2 K. Smoother hydraulic conditions also minimized valve noise and mechanical stress. These advantages are illustrated in Figure 8, which shows the hydraulic behavior with differential pressure controllers [12,13].

3.2.2. Dynamic Control Using a Variable-Frequency-Drive Pump

Another level of dynamic regulation is the replacement of a fixed-speed pump with a variable-frequency-drive (VFD) pump. For standard two-pipe systems, the most suitable settings are proportional pressure control (Figure 9D) or constant pressure control (Figure 9B).

The operating principle of VFD-controlled pumps is depicted in Figure 9, while the relation between flow rate and pumping power under dynamic conditions is presented in Figure 11 [18].

In Figure 10, the system is similar to the statically regulated system shown in Figure 7. The difference lies in the use of a variable-frequency-drive (VFD) pump, which is set to proportional pressure control according to Figure 9D. The purpose of proportional regulation arises from the problem of flow variation described in Figure 6. By adjusting the pump, the original operating curve (indicated by a red dashed line, Figure 10) is replaced by a solid red line. The pump, equipped with a differential pressure sensor, responds to changes in flow caused by the thermostatic heads. When the flow decreases, the pump reduces its output (head). The pressure throttled at the thermostatic valve is shown as the red area, remaining within the optimal control range. Proper system performance is always conditioned by accurate design and correct parameter settings. This strategy led to a reduction in pumping electricity consumption by 30–38%.

Advantages of dynamic heating control

• Energy efficiency: the system optimizes energy consumption by delivering only as much heat as is needed.
• Higher thermal comfort: the system adapts to outdoor temperature, indoor conditions, and user preferences.
• Automatic adaptation: it responds to temperature changes in real time, reducing temperature fluctuations.

Disadvantages of dynamic heating control

• Higher investment costs.
• More complex installation and configuration.
• Possibility of technical failures.
• Dependence on electricity.
• Security risks associated with intelligent control.
• Need for maintenance and software updates.
• Complexity for less technically skilled users.
• When using a pump without a frequency converter, throttling leads to wasted pumping energy.

Despite these drawbacks, dynamic control provides users with long-term and higher comfort, while many potential issues can be minimized through proper system design and configuration.

3.3. The Effect of Operating Temperature Regimes

The choice of operating regime significantly influenced seasonal efficiency and renewable compatibility. At 70/50 °C, return temperatures often exceeded 55 °C, limiting condensing-boiler efficiency and amplifying distribution losses. Shifting to 65/55 °C extended the condensing regime to approximately −9 °C outdoor temperature, thereby improving seasonal performance compared with −5.5 °C at 70/50 °C [11,19]. The proportional-pressure control curve used in this evaluation is presented in Figure 11.

For each pump, we can apply the laws of proportionality to a good approximation.

Volume flow (V) is proportional to the number of revolutions (n)

$${\displaystyle \frac{V1}{V2}}={\displaystyle \frac{n1}{n2}}$$

The delivery height (H) is proportional to the square of the number of revolutions (n).

$${\displaystyle \frac{H1}{H2}}={\left({\displaystyle \frac{n1}{n2}}\right)}^2$$

The electrical power (P) is proportional to the third power of the number of revolutions (n).

$${\displaystyle \frac{P1}{P2}}={\left({\displaystyle \frac{n1}{n2}}\right)}^3$$

Figure 11a shows that when the flow rate V (speed) decreases from 100% to 50%, the electrical power input of the pump P decreases to about 15–20%. Depending on the type, characteristics of the pump, … Figure 11b shows the dependence of the pump discharge head H on the water flow rate V. Figure 11c shows the decrease in electrical power input P on the pump flow rate V.

The 40/30 °C (in new buildings (floor, wall, and ceiling heating systems) regime delivered the greatest benefits, enabling integration of heat pumps and solar thermal energy without loss of comfort. These effects are illustrated in Figure 12, which combines weather-compensated supply regulation with dynamic pump control.

In all cases shown in Figure 12, the heat source is a weather-compensated heat transfer station (HTS). Currently, the most common control method is shown in Figure 12c. The most suitable configuration, however, is illustrated in Figure 12d, where the weather-compensated control unit can regulate both qualitatively—by adjusting the supply water temperature—and quantitatively—by controlling the building’s circulation pump. This approach assumes that the HTS provides heating water with sufficient temperature potential. Weather-compensated control is mainly used when multiple circuits with different temperature gradients or different heating time schedules are connected to a common heat source.

3.4. When Problems Occur in the Hydraulics of Building Heating Systems

In newly constructed buildings with properly designed heating systems, it is generally assumed that no operational issues will arise. The designer takes into account all known system parameters and operational requirements. The situation becomes more complex, however, when an existing building connected to a centralized heat source undergoes thermal insulation, as shown in Figure 1 for buildings “B” and “C.” Insulation has a significant impact on the heating system. Experience shows that heat demand typically decreases by 30–60%. Internal heat gains usually remain unchanged, which means their share in the building’s total heat balance increases substantially representing an additional factor affecting system operation. Adjustment methods are used for heating systems when the heat source remains unchanged.

Quantitative control (reduction in heating water flow rate—Figure 1, building “B”).

The design principles and interrelations have been described in previous chapters. A reduction in flow rate causes an increase in the temperature differential, which consequently lowers the radiator output. According to Figure 13, a 60% reduction in heating output corresponds to a flow rate reduction to approximately 15% of the original value. Such a drastic decrease in flow may cause existing components (e.g., preset thermostatic valves) to operate outside their control range (see Figure 7). Regulation then becomes discontinuous, noise may occur, and fittings may become damaged. The optimal throttling pressure for thermostatic valves is approximately 6–10 kPa. After insulating a building, it is necessary to reconsider the rebalancing of the internal heating distribution system. Adjustment at the heating system inlet can be achieved through dynamic control methods, as shown in Figure 12b,c.

The impact on end-user comfort is highlighted in Figure 13, showing radiator heat output as a function of flow rate [23].

A more advantageous solution at the building inlet is the use of weather-compensated control, as shown in Figure 12d. This type of control allows heating according to the building’s own heating curve and requires minimal intervention in the internal hydraulic distribution system. If necessary, the water flow rate can also be adjusted by the building’s circulation pump, making the regulation both qualitative and quantitative at the same time.

During the operation of weather-compensated control, as shown in Figure 14, the following modes are compared:

-

“A”—normal operation,

-

“B”—extreme mode with maximum heat demand from the HTS,

-

“C”—mode without heat extraction from the HTS.

The modes A, B, and C are intentionally presented in the figure to ensure that all operating states are considered during system design to guarantee trouble-free operation. A crucial role in stable operation is played by the characteristics of the three-way mixing valve, the control method of the building circulation pump, and the control valve located at the building inlet.

The system is adjusted so that the differential pressure across the thermostatic valves remains between 6–10 kPa. The building pumps and the heat source pump operate in series. In mode “A,” the operation of the source pump is partially throttled by the mixing valve. In mode “B,” the effect of the three-way valve is minimal, and the pump pressures are additive. In mode “C,” the three-way valve is closed, isolating the influence of the heat source pump, and the building’s hydraulics are ensured solely by the local circulation pump.

If the system is improperly designed or operated in mode “B,” the combined pressure of both pumps may cause excessive differential pressure, resulting in noise and unstable valve operation. In mode “C” (setback mode), the local circulation pump alone may not be sufficient to maintain proper hydraulic performance within the building. The actual system operation typically occurs within the range between modes “B” and “C”.

Special attention should be paid to the method of pressure sensing on the pump, as shown in the figure. If it is not possible to use a pump with remote pressure sensors, a combination with additional differential pressure control fittings may be applied, or the local circulation pump can be operated under proportional pressure control (Figure 9D). It is also necessary to consider the presence and placement of filters, flow meters, and other system components that may adversely affect proper functionality. There are many possible design solutions; however, their detailed description lies beyond the scope of this paper.

3.5. Thermal–Hydraulic Separation and Storage

In systems with multiple active heat sources or consumers with variable demands, mutual hydraulic interference between pumps is eliminated by using hydraulic separators. The evaluation of hydraulic separation devices highlighted contrasting outcomes. Hydraulic separators (HS) provided hydraulic decoupling but induced mixing effects that degraded supply temperatures, particularly under partial-load operation. In the simulations, this increased return temperatures by 3–5 K, reducing condensing-boiler efficiency [15]. A typical multi-source DHS configuration with a hydraulic separator is shown in Figure 15.

Throughout the year, the heat demand for space heating varies. The utilization of heat sources is as follows:

Example according to Figure 15b:

-

Operation of the heat source with 1 boiler = approx. 30 days;

-

Operation of the heat source with 2 boilers = approx. 185 days;

-

Operation of the heat source with 3 boilers = approx. 15 days.

On the primary side, the heat demand also fluctuates. The varying operation of the equipment causes hydraulic imbalance due to the mutual interaction of the pumps. The standard hydraulic solution is the use of a hydraulic separator (anuloid). The anuloid primarily serves to eliminate the mutual hydraulic influence of pumps. However, it has an unfavorable effect on temperature conditions, as water mixing occurs inside the separator, leading to a reduction in the temperature of the heating water. This makes it unsuitable for use with condensing boilers or heat pumps, as these sources must operate at higher temperature ranges. The relationship of these temperature conditions corresponds to the heating water temperatures shown in Figure 2.

In contrast, buffer tanks delivered dual benefits: hydraulic decoupling and thermal inertia. By absorbing fluctuations in both demand and renewable input, buffer tanks stabilized ΔT and improved renewable utilization. Their comparative performance, relative to hydraulic separators, is illustrated in Figure 16 [16,17].

The measurements were performed using the calorimetric method, and the graphs present only the temperatures and average flow rates during the defined time interval.

Case 1—Standard and energy-optimal operating mode (Figure 16b)

The most common configuration in operation corresponds to Figure 16b, which also represents the designed state (Figure 15). In this mode, two boilers operate for approximately 185 days of the heating season. The flow rate of the heating medium on both the primary (Pf) and secondary (Sf) sides is identical, minimizing the mixing of supply and return water within the hydraulic separator (HS). The temperature differences between the supply branches (T1–T3) and return branches (T2–T4) are minimal, allowing the heat sources to operate under optimal temperature conditions with high energy efficiency.

Case 2—Operation with a single heat source (Figure 16c)

When only one heat source is operating, which typically corresponds to about 30 days of annual operation, a mismatch between the flow rates occurs—the flow on the primary side (Pf) is lower than on the secondary side (Sf). As a result, significant water mixing takes place within the HS, causing a decrease in the outlet temperature T3. This decrease can be compensated only by increasing the inlet temperature T1. However, higher T1 requirements may lead to boiler operation outside the condensing range or even exceed the temperature limits of the heat pump. Even if the heat pump capacity is sufficient, the system may become non-functional or significantly less efficient if it cannot reach the required outlet temperature.

Case 3—Operation with three heat sources (Figure 16a)

In the mode with three active heat sources (approximately 15 days per year), the flow rate on the primary side (Pf) is higher than on the secondary side (Sf), causing internal mixing within the HS and an increase in the return temperature T2. The elevated T2 forces the heat sources to operate at a higher temperature level, thereby reducing their efficiency.

Function of the hydraulic separator and options for its replacement

The primary function of the hydraulic separator (HS) is to eliminate the mutual influence of circulation pumps in the system, contributing to the stability of hydraulic conditions. However, the drawback of this solution is the potential for intensive mixing between the supply and return branches, depending on the current flow conditions. In extreme cases, the degree of mixing may become so undesirable that it prevents the HS from being effectively used. An alternative solution is to replace the HS with a buffer tank. The key difference between these two devices lies in the water volume and the spacing of the connected branches. While the HS does not provide storage capacity and tends to exhibit higher mixing, a properly designed buffer tank ensures minimal mixing while maintaining the required hydraulic independence of the pumps.

3.6. Energy and Emissions Reduction Potential

When the results are considered cumulatively, the benefits of modernization become evident. Dynamic regulation combined with optimized ΔT and renewable integration yielded 30–40% reductions in pump energy, 7–17% improvements in delivery efficiency, and lifecycle CO₂ reductions of up to 77%. These results are consistent with 4GDH and 5GDHC frameworks reported in recent European case studies [5,6,8,9,33,34]. A summary of the comparative results across static and dynamic regulation modes under different temperature regimes is provided in

Table 2. Comparative results of static vs. dynamic regulation across temperature regimes.

Operating Regime	Regulation Type	Pump Energy Use	ΔT Stability	Delivery Efficiency	CO2 Reduction Potential
70/50 °C	Static	100% (baseline)	5–8 K fluctuation	~82%	–
	Dynamic	−20 to −25%	±2 K	~88–89% (+6–7%)	up to 15%
65/55 °C	Static	100% (baseline)	5–7 K fluctuation	~84%	–
	Dynamic	−25 to −30%	±2 K	~90–91% (+7–8%)	up to 25%
40/30 °C	Static	100% (baseline)	4–6 K fluctuation	~86%	–
	Dynamic	−30 to −38%	±1–2 K	~96–97% (+10–11%)	up to 77%

.

4. Discussion

The findings of this study confirm that dynamic regulation fundamentally alters the performance of district heating systems. By maintaining ΔT stability and reducing throttling, variable-frequency-drive pumps and weather-compensated control delivered energy savings of up to 38%. These results demonstrate that advanced regulation not only improves local comfort but also contributes to systemic efficiency by lowering return temperatures and enabling renewable integration. The combined effect is a substantial improvement in exergy performance, which has long been recognized as a bottleneck in conventional DHS [19].

Importantly, the transition from 70/50 °C to 40/30 °C operation revealed a step change in sustainability outcomes. At low-temperature regimes, dynamic regulation allowed for effective coupling with heat pumps and solar thermal systems, reducing lifecycle CO₂ emissions by up to 77%. Depending on the scope and type of renewable energy sources used, CO₂ savings can reach up to 77%. This aligns with 4GDH frameworks emphasizing that low-temperature operation is indispensable for meeting carbon neutrality targets [5,6,11].

4.1. Comparison with Previous Studies

Our results are in line with earlier experimental studies which showed that static regulation leads to higher return temperatures and as much as 30% extra primary energy use [21,22,23]. Reported savings of 25–35% from dynamic regulation [12,13] also agree well with the 30–38% reductions we obtained. In addition, the findings are consistent with evidence from Scandinavian pilot projects, where low-temperature operation was identified as a key condition for integrating intermittent renewables [18,30].

This work adds to the literature by showing how hydraulic optimization and dynamic regulation can work together. Previous studies usually examined balancing methods [29,40] or control strategies [24,25,26,27,28] separately, while our results suggest that their combination provides larger gains in both efficiency and CO₂ reduction. The comparison of hydraulic separators and buffer tanks also contributes to the ongoing discussion about the most effective approach for multi-source DHS. Here, our results support recent simulations and field studies indicating that buffer tanks perform better than hydraulic separators in maintaining stable supply temperatures [15,16,17].

4.2. Practical Implications and Policy Relevance

Our results have several practical implications for both system operators and policymakers. For operators and municipalities, three points are especially important. First, retrofitting static networks with dynamic control should be prioritized, as it delivers immediate efficiency gains and greater operational stability without the need for large infrastructure investments. Second, a gradual transition to low-temperature regimes is essential to enable renewable integration and to maintain compatibility with future 4GDH standards [5,8,9]. Third, buffer tanks should be promoted as best practice in multi-source systems, since they provide both hydraulic separation and thermal storage [15,16,17].

For policymakers, the results underline the importance of linking building retrofits with district heating modernization. Without hydraulic optimization, insulated buildings may create imbalances that prevent low-temperature operation [21,29]. Policy instruments and support schemes should therefore combine building-side measures with network-side improvements, ensuring consistent progress toward climate neutrality [2,7,8].

Efforts to optimize the operation of distribution systems by reducing temperature gradients, using various materials, and applying storage tanks can lead to new operational issues. The root cause is an incorrect combination of these factors in relation to the physicochemical composition of the heating medium or water. This may result in material degradation within the system, the formation of deposits leading to clogging of pipelines, fittings, and equipment. Low temperatures also promote bacterial growth (e.g., Legionella in hot water systems), the development of biofilms on pipe walls, and the precipitation of chemical compounds. Therefore, it is essential to place great emphasis on the quality of the filling medium and, based on diagnostics, apply appropriate cleaning of the distribution system and equipment.

4.3. Limitations and Future Research

This study has several limitations that need to be acknowledged. It is designed for secondary heat distribution systems and is based primarily on residential buildings (apartment houses).

The simulations were based on simplified thermo-hydraulic models that, while representative, cannot fully capture the variability of real operating networks.

Over a period of approximately 30 years, we have gradually designed and monitored the development of systems—from simpler configurations with static control, using fittings and devices typical of their time, to the present-day systems employing dynamic regulation. The current approach seeks to apply the best available technical solutions at acceptable costs while maintaining economic efficiency. In buildings, we design solutions with data collection and energy system control through predictive algorithms, aiming to transform buildings into “smart buildings.” In practice, compromise solutions are often implemented, determined by financial constraints and residents’ willingness.

In the studied buildings, a series of technical measures have been gradually implemented to enable users to influence their own energy consumption. These include insulation of the building envelope, hydraulic balancing, and control of heat supply to the buildings. All these measures gained importance once consumers were motivated by the installation of metering devices on apartments or heating radiators. However, the introduction of metering brought additional challenges related to heat cost allocation, considering apartment location, orientation, occupancy, and the age structure of residents.

All these measures directly or indirectly affect the hydraulic performance of buildings and often require a change in the concept of heat supply control. The share of passive heat gains has significantly increased, frequently leading to the complete closure or disconnection of heating radiators. This highlighted the issue of heat transfer between apartments and its consideration in heat and domestic hot water billing. As heating demand decreases, the proportion of energy consumption for domestic hot water has increased substantially—a factor not considered in this study.

Future research should therefore move beyond modeling and include long-term monitoring of actual networks to validate the results presented here. Pilot projects that combine MPC algorithms, buffer storage, and renewable integration in real urban settings would provide valuable empirical data. Expanding the scope towards cross-sector coupling—for example, linking heating with demand-response in electricity systems—could also reveal additional synergies relevant to the ongoing energy transition.

4.4. Policy and Sustainability Implications

The modernization of district heating systems through dynamic regulation, hydraulic optimization, and renewable integration directly supports SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action). By lowering distribution temperatures and stabilizing supply–return differentials, networks can achieve higher efficiency and measurable CO₂ savings, in line with the Paris Agreement targets [1,3,7,8,42,43,44,45,46,47,48,49,50].

At the EU level, the Green Deal and the revised Energy Efficiency Directive identify heating decarbonization as a priority sector. Our results suggest that dynamic regulation and low-temperature operation are prerequisites for compliance with these frameworks. Policy instruments should therefore support combined interventions: building insulation on the demand side and dynamic control with buffer storage on the supply side.

For municipalities, three measures are particularly relevant: (i) retrofit static networks with dynamic pumps, (ii) promote 40/30 °C regimes to enable renewable heat, and (iii) adopt buffer tanks in multi-source networks. Together, these measures reduce energy costs for consumers and improve resilience against fossil-fuel price volatility.

Finally, DHS modernization should be considered part of systemic urban energy planning rather than isolated upgrades. Linking heating with renewable electricity, demand-response, and digital control offers additional synergies that are crucial for low-carbon cities.

5. Conclusions

This study focused on three key objectives:

• To compare static and dynamic control of heating systems in multiple variants and identify their operational advantages and limitations;
• To analyze the impact of temperature differences on network hydraulics, pumping energy, and the potential for integrating renewable energy sources;
• To examine weather-compensated control methods for multi-source systems and their connection to district heating networks.

The results obtained from secondary hot-water distribution systems confirm that dynamic control using variable frequency drive (VFD) pumps and weather-compensated heat supply management lead to stabilized temperature differentials (ΔT) and a reduction in pumping energy consumption by up to 38%. In contrast, static control under mixed demand, decreasing heat requirements, or the integration of new heat sources cannot ensure stable operation, resulting in fluctuations in return water temperature and a decrease in overall system efficiency.

The analysis of temperature differences highlights their fundamental influence on both hydraulic behavior and the system’s energy intensity. Optimization of the temperature regime supports the integration of renewable sources and facilitates the transition toward fourth-generation district heating systems. Operating secondary networks at low temperatures (e.g., 60/40 °C or lower) enables efficient utilization of heat pumps and solar systems and reduces CO₂ emissions over the life cycle by up to 77%, depending on the type and extent of renewable energy use.

The integration of new heat sources into the secondary network is carried out through heat exchangers, hydraulic separators, or buffer tanks. Buffer tanks have proven to be the most suitable solution, as they ensure not only hydraulic separation but also thermal energy storage, minimizing negative impacts on the network. All approaches and design recommendations depend on the specific system conditions and the related technical and economic feasibility.

The findings from secondary networks also indicate the need to optimize primary distribution systems, particularly by reducing supply and return temperatures and implementing predictive control based on weather forecasting. The integration of renewable energy sources on the primary side is limited by high operating temperatures and is therefore most suitable for biomass, cogeneration, waste incineration, and geothermal systems.

Overall, the study confirms that the combination of hydraulic optimization, dynamic control, and weather-compensated management provides an effective framework for the modernization of district heating systems and for reducing their carbon footprint. Future research should include long-term monitoring of real networks, the development of predictive control, and the integration of thermal and electrical systems based on renewable energy sources.