Domestic hot water load profiles strongly influence heat exchanger sizing. Learn how flow patterns, peak demand behaviour and regime-changing components affect power requirements and ΔT stability.
DHW systems often experience short but intense peaks. These demand spikes determine how much thermal power must be transferred across the heat exchanger, especially in instantaneous or HIU-based designs.
Because real draw-off behaviour rarely matches theoretical assumptions, heat exchanger sizing must reflect how users actually consume hot water — not just nominal ratings. A realistic representation of these patterns ensures that DHW systems deliver stable temperatures without oversizing the primary network.
Heat exchangers react dynamically to flow changes, meaning power demand at the primary side depends heavily on how DHW flows evolve during use.
The behaviour captured in step 3 DHW flow and power calculation shows how regime changes — such as switching from low to high DHW draw-off — impact temperature lift, primary flow and required thermal power.
If the primary side cannot supply sufficient flow or temperature during these transitions, DHW temperatures drop and comfort is affected. Correctly modelling these transitions is essential to determine the true required exchanger capacity.
The performance of heat exchangers depends on both thermal and hydraulic conditions. Load profiles influence:
Heat exchangers with insufficient capacity may maintain setpoint at moderate flows but struggle under peak taps. Conversely, oversized units can erode ΔT, increasing return temperatures and reducing production efficiency.
Matching the exchanger’s transfer area and UA value to realistic DHW patterns ensures predictable operation across all draw-off scenarios.
A well-designed DHW installation must tolerate rapid load variations without sacrificing comfort or efficiency. This means verifying that the chosen heat exchanger can maintain outlet temperature under both typical and extreme tap events.
Engineers should evaluate:
Correct sizing based on realistic profiles results in lower energy cost, more stable temperatures and a system that behaves predictably throughout the day.
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