## 3 Discussion
Consequently, advanced control paradigms such as inferential control or delta T feedback schemes present promising avenues for improving system responsiveness and maintaining occupant comfort. Achieving more refined system-level optimization in large-scale DH networks necessitates both advanced control techniques and tightly coordinated operations across all network components to accommodate fluctuating heat demand and supply. Adopting variable-flow strategies in place of static flow rates is especially pivotal: beyond merely reducing pumping energy, dynamically adjusting flow rates in response to load profiles(while ensuring control valves can operate effectively at low flows) contributes to consistently lower return temperatures. Moreover, while weather compensation curves are widely employed, their efficacy hinges on proper commissioning and real-time indoor feedback. Recent studies recommend more adaptive approaches, such as inferential or delta T-based control, which better match supply temperatures to the instantaneous needs of both buildings and the broader network, thereby minimizing risks of overheating at end-user installations. In large-scale systems, an additional challenge arises when local inefficiencies, such as imbalanced flow or improperly tuned valves, lead to widespread return temperature elevations. Precise coordination--through well-calibrated thermostatic and control valves, together with suitably specified pump characteristics--helps mitigate these \"hotspots\", thereby enhancing system-wide efficiency. For networks confronted with large load swings, the strategic use of heat storage solutions can further buffer peaks and reduce unnecessary bypass flow, using any surplus effectively instead of reintroducing it into the return line at high temperatures. Through a combination of advanced control schemes, rigorous hydraulic balancing, and dynamic storage usage, large-scale DH networks can maintain both operational reliability and robust return temperature reduction, even under highly variable load conditions. Research indicates that a lower return temperature combined with a reduced flow rate has a beneficial effect near the heat source. From a network-centric perspective, incorporating renewable energy sources (e.g., solar thermal fields, biomass, and geothermal wells) into DH systems does not inherently guarantee lower return temperatures. While renewables reduce fossil fuel dependency and mitigate carbon emissions, they primarily influence supply-side generation rather than return-line thermodynamics. Instead, the return temperature is governed by internal system design and operation, encompassing hydraulic configurations, substation technologies (e.g., instantaneous versus storage-based heat exchangers), control mechanisms such as weather compensation or delta T feedback, and end-user practices. Consequently, the decisive levers for minimizing return temperatures lie in rigorous hydraulic balancing, advanced flow control schemes, and the precise calibration of consumer-side valves and thermostats. The renewable energy installations, albeit vital for decarbonizing the system, play a relatively peripheral role in actively reducing return temperatures; the system's ability to manage flow rates, distribution temperatures, and end-user interactions ultimately determines whether low-return-temperature targets are met. Exhaust-gas condensation units are particularly sensitive to the DH return temperature, as they achieve higher heat recovery with lower return temperatures. Consequently, some DH systems intentionally increase the supply temperature to achieve a lower return temperature, thereby enhancing heat recovery at their condensing units. When considering cogeneration units, it is important to recognize that maintaining a low temperature at the condensers, which heat the DH water, reduces pressure and enhances steam flow through the turbine, thereby increasing electricity output.