Optimal management and operational control of urban sewer systems

Abstract

Combined sewer networks control, like many other real world problems, is usually identified with competing and conflicting objectives. Decision makers have a great need of selecting the best possible control strategy in minimizing the combined sewer overflows (CSOs) when controlling the sewer networks. However, this control strategy should be cost effective to produce a feasible control approach in real world. Cost effectiveness has become significantly important in present economic recession. Over the past decades, people have witnessed the control strategies based on minimization of CSOs. However, it is now, not only to minimize CSOs, but also to minimize the impact to the natural water from these CSOs. Therefore, this research explores the development of a holistic framework that is used for the multi-objective optimization of urban wastewater systems, considering flows and water quality in combined sewers and the cost of wastewater treatment. Pollution levels of several water quality parameters in dry weather flows and stormwater runoff are considered. Pollutographs for several water quality parameters are generated for the stormwater runoff. Temporal and spatial variations of the stormwater runoff are incorporated using these pollutographs for different land-uses. Furthermore, pollutographs are developed for different storm conditions, including single, two consecutive and migrating storms. Evolutionary algorithms are extensively used in solving the developed multiobjective optimization approach. Formulations for two different optimization approaches, one for the snapshot optimization and the other one for the dynamic optimization are developed. Simulation results from a full hydraulic model, including water quality routing are used in the optimization. The performance of the multi-objective optimization models are tested on a simple interceptor sewer system for several storm conditions. The proposed optimization approach for snapshot optimization gives the optimal CSO control settings where a single set of static control settings is used throughout the considered time period. However, the proposed optimization approach for dynamic optimization is capable of producing control strategies over the full duration of storm period. Furthermore, results for a number of alternative formulations in constraint handling for the developed multi-objective optimization approach are compared. They produce interesting findings. Overall, the constraint handling formulations developed outside the genetic (NSGA II) algorithm provides better control in combined sewer networks. In addition, the results of the multi-objective optimization demonstrate the benefits of the usage of optimization approach and its potential to establish the key properties of a range of control strategies through an analysis of the various tradeoffs involved. Solutions from the dynamic optimization approach highlight the usage of the real-time control in combined sewer systems. Given that the technology is there to measure water quality and flow rates, collect data and send feedbacks to the sewer system through central processing unit and the usage of high performance computers, the developed optimization model is capable of handing the present society's concerns in combined sewer systems. The model is capable of controlling the existing sewer networks according to the receiving water regulations and the fund availability of the wastewater treatment plants. However, further research is required to apply the developed multi-objective optimization approach in real-time control of urban sewer systems.