Abatement of Sewer Overflow Pollution Based on Distributed Optimal Control Approach

Optimal control is promising to mitigate the pollution from combined sewer overflows during wet-weather days. In this study, a distributed optimal control approach to regulating multipoint controlling units of the urban sewer system was developed. By introducing a differential evolution algorithm with ranking-based mutation operators, good simulation results with lower overflow mass loadings can obtain higher evolutionary probabilities. Thus, the optimal solutions to minimize the overflow mass from a large sewer network can be efficiently obtained. The developed approach was demonstrated in a catchment (total coverage area of 22.4 km2) served by one wastewater treatment plant in Chaohu City, Anhui Province of China, with five pumping stations and 18 associated sewage or stormwater pumps as the distributed controllers. After a global optimization among various controlling units, performance of the sewer network in reducing its overflow was improved obviously through fully utilizing in-sewer storage and adjusting the sewer flow transportation harmoniously (i.e., an alternative mode of full storing and fast transportation in sequence). Accordingly, the overflow volume and the overflow mass loading of total nitrogen was reduced by 32.3% and 37.6%, respectively, without retrofitting the current sewer network. On the basis of the presented approach, decision-makers can develop a database for optimal regulation of sewer network under various rainfall scenarios and respond to sewer overflow control flexibly and cost-effectiveness.