A Simulation-Based Framework for Energy-Efficient and Safe Blower Coordination in Wastewater Treatment Plants

Luca Cirillo, Marco Gotelli, Marina Massei, Xhulia Sina and Vittorio Solina ()
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Luca Cirillo: Dipartimento di Ingegneria Meccanica, Energetica, Gestionale e dei Trasporti, University of Genoa, Via Opera Pia 15, 16145 Genova, Italy
Marco Gotelli: Dipartimento di Ingegneria Meccanica, Energetica, Gestionale e dei Trasporti, University of Genoa, Via Opera Pia 15, 16145 Genova, Italy
Marina Massei: Dipartimento di Ingegneria Meccanica, Energetica, Gestionale e dei Trasporti, University of Genoa, Via Opera Pia 15, 16145 Genova, Italy
Xhulia Sina: Dipartimento di Ingegneria Meccanica, Energetica, Gestionale e dei Trasporti, University of Genoa, Via Opera Pia 15, 16145 Genova, Italy
Vittorio Solina: Department of Mechanical, Energy and Management Engineering, University of Calabria, Ponte Pietro Bucci–Cubo 45/C, 87036 Rende, Italy

Energies, 2025, vol. 18, issue 22, 1-17

Abstract: Wastewater treatment plants (WWTPs) are critical infrastructures that account for a significant share of global electricity, with aeration alone often responsible for over half of the total demand. Reducing the energy intensity of blower operation is, therefore, essential for sustainable and resilient WWTP management. This study presents a modeling and simulation framework for optimizing parallel blower operation in grit chamber aeration system. The framework integrates a modular structure with a blower model, a distribution network model, and an optimization layer that work together to capture equipment performance, simulate hydraulic interactions, and determine energy-optimal operating strategies under process and safety constraints. Two optimization strategies are compared: a heuristic grid search and a Safe Bayesian Optimization (SBO) method. Both algorithms enforce vendor surge and overheat limits, network pressure constraints, and process requirements. Simulation campaigns under representative demand scenarios show that both approaches achieve feasible operating points, while SBO consistently demonstrates higher energy savings and substantially faster runtime. Overall, the findings highlight the potential of data-driven optimization for achieving efficient and safe blower control, with reduced computation time making progress for real-time supervisory optimization in WWTPs.

Keywords: wastewater treatment plants (WWTPs); aeration blowers; energy efficiency; grid search optimization; sustainable operations management (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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