Optimised operation of sewage pumping stations: a systematic review

Sewage pumping stations (SPS) are core assets in wastewater collection systems whose operations are constrained by stochastic inflows, limited wet-well storage, downstream receiving capacity, cycling limits, and overflow risk. This systematic review, reported in accordance with PRISMA, synthesises 29 peer-reviewed studies on SPS operational optimisation. Across the corpus, methods progress from reactive level-based control towards optimisation and control frameworks that combine forecasting, explicit constraint handling, and data-driven policy design (including model predictive control and reinforcement learning). Reported energy outcomes range from incremental gains of about 3–4% under minor control refinements to more typical reductions of approximately 15–32% in studies using predictive scheduling/optimisation, with isolated cases above 70% in specific test configurations relative to the selected baseline. Beyond energy, several studies report reductions in pump starts, alarms, and combined sewer overflow metrics, highlighting the need to treat SPS operations as a multi-objective problem (energy/cost, wear, detention time, sedimentation propensity, and overflow). Variable frequency drives expand the feasible control space but do not yield benefits without control policies that target appropriate operating regions. Implementation evidence remains limited: most results rely on simulations or short pilots, and adoption is constrained by data quality, computational feasibility for real-time use, integration/commissioning costs, and organisational risk management. Priority directions include uncertainty-aware control, robust hybrid modelling, scalable coordination at network scale, and long-duration field validation.