Maximising Heat Recovery Potential in Sewer Networks Using a Quasi-Steady-State Optimisation Framework

Decarbonising domestic heating stands as one of the primary climate challenges, positioning net-zero building technologies as the vital technical response. Wastewater source heat pumps (WWSHPs) serve as a thermally stable solution for household heating. Scaling this system up to an urban network level requires balancing maximum heat extraction against the risks of biological damage to downstream treatment systems from excessive temperature drops. To resolve it, this study couples a quasi-steady-state model, driven by dynamic, 30 min time-series inputs, with a Genetic Algorithm (GA) to optimise a 41-pipe sewer network in Belgium. Significant results demonstrate that the GA configuration enhanced potential heat recovery by 51.7% relative to unoptimised baselines, elevating yields from 29 MW to 44 MW. Furthermore, this research identified a mass compensation effect in winter that effectively counterbalanced seasonal drops in wastewater temperature, resulting in nearly identical winter and summer average heat recovery capacities (17.409 MW vs. 17.492 MW, a variance under 0.5%). From these findings, it can be concluded that while network-scale thermal potential is exceptionally robust year-round, a profound seasonal mismatch exists between available supply and localised consumer heating requirements, which drop to a minimum of 712 kW in July but exceed 51 MW in winter.