Predictive optimal control of sewer networks using CORAL tool: application to Riera Blanca catchment in Barcelona

Model predictive control of stormwater basins coupled with real-time data assimilation enhances flood and pollution control under uncertainty

Smart stormwater systems equipped with real-time controls are transforming urban drainage management by enhancing the flood control and water treatment potential of previously static infrastructure. Real-time control of detention basins, for instance, has been shown to improve contaminant removal by increasing hydraulic retention times while also reducing downstream flood risk. However, to date, few studies have explored optimal real-time control strategies for achieving both water quality and flood control targets. This study advances a new model predictive control (MPC) algorithm for stormwater detention ponds that determines the outlet valve control schedule needed to maximize pollutant removal and minimize flooding using forecasts of the incoming pollutograph and hydrograph. Comparing MPC against three rule-based control strategies, MPC is found to be more effective at balancing between multiple competing control objectives such as preventing overflows, reducing peak discharges, and improving water quality. Moreover, when paired with an online data assimilation scheme based on Extended Kalman Filtering (EKF), MPC is found to be robust to uncertainty in both pollutograph forecasts and water quality measurements. By providing an integrated control strategy that optimizes both water quality and quantity goals while remaining robust to uncertainty in hydrologic and pollutant dynamics, this study paves the way for real-world smart stormwater systems that will achieve improved flood and nonpoint source pollution management.

Operational reliability of urban drainage systems under uncertainties

Water quality risks from overflows have attracted significant research attention, and the reliability of urban drainage systems (UDS) is in urgent need of assessment and improvement. The overflow volume and concentration of critical pollutants are generally used as assessment indicators, which is quite time consuming and cumbersome especially under continuous rainfall. Simplifying the water quality risk assessment indicators for the UDS reliability is intractable. For this purpose, this study proposes the detention tank emptying time as a new reliability evaluation indicator, which greatly reduces the calculation burden by converting water quality risk into hydraulic risk. On this basis, the effects of rainfall, dry weather flow (DWF), actuators and their interactions on reliability are quantified by massive scenarios. It shows that the DWF affects the emptying process via weekly and daily seasonality and its interaction with rainfall is mainly responsible for unreliability. Further, the engineering facility linkage controlled by the actuator to cope with the interaction is the key. Particularly, the Prophet algorithm is innovatively applied to mine the patterns and generate the DWF series for the challenge of sparse DWF data. In conclusion, the indicator proposed expands the connotation of UDS reliability assessment, prompting a small investment in replacing actuators with better controllability and greatly improving reliability. It guides the engineering planning and enhancement from a new perspective of whole-chain optimization from the global to the detailed level.

Towards the long term implementation of real time control of combined sewer systems: a review of performance and influencing factors

Real Time Control (RTC) is widely accepted as a cost-effective way to operate urban drainage systems (UDS) effectively. However, what factors influence RTC efficacy and how this might change in the long term remains largely unknown. This paper reviews the literature to understand what these factors likely are, and how they can be assessed in the future. Despite decades of research, inconsistent definitions of the performance of RTC are used, hindering an objective and quantitative examination of the benefits and drawbacks of different control strategies with regard to their performance and robustness. Furthermore, a discussion on the changes occurring and projected to occur to UDS reveals that the potential impact of these changes on the functioning of RTC systems can be significant and should be considered in the design stage of the RTC strategy. Understanding this 'best-before' characteristic of an RTC strategy is the key step to ensure long term optimal functioning of the UDS. Additionally, unexplored potential for RTC systems might exist in the transitions, rehabilitation and construction of drainage systems. The research gaps highlighted here could guide the way for further development of RTC strategies, and enabling more optimal, long term implementation of RTC for urban drainage systems.

Control-oriented quality modelling approach of sewer networks

A control-oriented quality modeling approach is proposed for sewer networks, which can represent quality dynamics using simple equations in order to optimize pollution load from combined sewer overflows in large scale sewer network in real time. Total suspended solid has been selected as the quality indicator, regarding it is easy to be estimated through measuring turbidity and correlated with other quality indicators. The model equations are independent for different elements in sewer network, which allows a scalable usage. In order to ensure accuracy of the proposed models, a calibration procedure and a sensitivity analysis have been presented using data generated by virtual reality simulation. Afterwards, a quality-based model predictive control has been developed based on the proposed models. To validate effectiveness and efficiency of the modelling and optimization approaches, a pilot case, based on the Badalona sewer network in Spain is used. Application results under different scenarios show that the control-oriented modelling approach works properly to cope with quality dynamics in sewers. The quality-based optimization approach can provide strategies in reducing pollution loads in real time.

On the Use of a Real-Time Control Approach for Urban Stormwater Management

The real-time control (RTC) system is a valid and cost-effective solution for urban stormwater management. This paper aims to evaluate the beneficial effect on urban flooding risk mitigation produced by applying RTC techniques to an urban drainage network by considering different control configuration scenarios. To achieve the aim, a distributed real-time system, validated in previous studies, was considered. This approach uses a smart moveable gates system, controlled by software agents, managed by a swarm intelligence algorithm. By running the different scenarios by a customized version of the Storm Water Management Model (SWMM), the findings obtained show a redistribution of conduits filling degrees, exploiting the whole system storage capacity, with a significant reduction of node flooding and total flood volume.

Integrated pollution-based real-time control of sanitation systems

An integrated pollution-based real-time control (RTC) approach is proposed for a sewer network (SN) integrated with wastewater treatment plants (WWTPs) in a sanitation system (SS) to mitigate the impacts of pollution from combined sewer overflows (CSOs) on ecosystems. To obtain the optimal solution for the SS while considering both quantity and quality dynamics for multiple objectives, model predictive control (MPC) is selected as the optimal control method. To integrate SN and WWTP management, a feedback coordination algorithm is developed. A closed-loop virtual-reality simulator is used to assess the results of the optimal management approach achieved by applying MPC. The Badalona SS (Spain) provides a pilot case study to assess the efficacy and applicability of the proposed approach. A comparison with local rule-based and volume-based control strategies currently in use indicates that the proposed integrated pollution-based RTC approach can reduce the pollutant loads released to the receiving environment.

Factors influencing the stormwater quality model of sewer networks and a case study of Louis Fargue urban catchment in Bordeaux, France

Pollution caused by combined sewer overflows has become a global threat to the environment. Under this challenge, quality-based real-time control (RTC) is considered as an effective approach to minimize pollution through generating optimal operation strategies for the sewer infrastructure. To suit the fast computation requirement of RTC implementation, simplified quality models are required. However, due to the hydrological complexity, it is not easy to develop simplified quality models which are amenable to be used in real-time computations. Under this context, this paper contributes a preliminary analysis of influencing factors for the quality models of sewer networks in order to give supportive knowledge for both model development and application. Conceptual quality models which were proposed previously by the authors, with total suspended solids (TSS) as quality indicator, are used in this study. A clustering algorithm is used for exploratory analysis. Further analysis about the correlations between different factors and model performance is also carried out. The study and analysis are demonstrated on a real pilot based on the Louis Fargue urban catchment in Bordeaux. Conclusive results about the influencing factors, flow rate, rain intensity and pipe length, as well as their correlations with the TSS models are elaborated.

Application of SWMM 5.1 in flood simulation of sponge airport facilities

Construction of an airport runway makes the impervious area of the airport high, which leads to the deterioration of the water environment and frequent waterlogging disasters. The selection of sponge airport facilities (e.g., pump, multi-functional storage tanks, green roof) to mitigate airport flooding has been a crucial issue in China. This study aims to develop a conceptual rainwater-runoff simulation model, which can take into account the effects of such facilities of a sponge airport. Taking catchment N1 of Beijing Daxing Airport as a case study, SWMM 5.1 was implemented to develop three sponge airport models (one pump, two pumps, combination of pump and multi-functional storage tanks). A sensitivity analysis was carried out to guarantee the robustness of the developed models. A 1-hour rainfall scenario with a 5-year return period was employed on the three sponge airport models. The results showed that the effect rankings of the control strategies on the water depth, volume and peak inflow of catchment N1 were comparable - combined strategies (combination of pump and multi-functional storage tanks) > one pump and two pumps. The conceptual and hydrological models developed in this study can serve as a simulation tool for implementing a real-time rainwater drainage control system in Beijing Daxing Airport.

Real-Time Control of Urban Water Cycle under Cyber-Physical Systems Framework

The urban water cycle (UWC), which is composed of the water supply system (WSS) and urban drainage system (UDS), is a critical infrastructure required for the functioning of urban society. Considering the growing pollution and subsequent water scarcity caused by increasing urbanization and climate change, efficient UWC management is required to maintain resource sustainability and environmental protection. Cyber-physical systems (CPSs) provide a technological suite for the efficient management of critical systems. To exploit advantages of CPS for UWC, this paper proposes a CPS-based management framework enabling supervision, subsystem interoperability, and integrated optimization of UWC: (1) Firstly, clear definitions are provided to demonstrate that UWC systems can be considered as CPSs. (2) A multi-layer CPS-based supervision framework is presented afterwards, conceptually dividing the physical UWC and its digital counterpart into Supervision&Control, Scheduling, Digital Twin, and Water Users and Environment four layers. (3) The information flows that interact with each layer, as well as a key aspect of CSP operation, namely the interoperability among subsystems in the context of UWC, are also addressed. (4) To demonstrate advantages of supervision and interoperability of subsystems under the CPS framework, an integrated optimizer based on model predictive control (MPC) is applied and compared against the individual control of each system. A real case study of the WSS and UDS in Barcelona UWC is applied in order to validate the proposed approaches through virtual reality simulations based on MATLAB/SIMULIN and EPA-SWMM.

Improving operational management of wastewater systems. A case study

Wastewater treatment facilities collecting wastewater from longstanding sewer networks of five municipalities in the Ave River basin (located in NW Portugal) are especially vulnerable to water inflows since they have considerable extensions of sewers installed in stream and riverbeds. TRATAVE, the company responsible for operating the system, designed and implemented a monitoring network to measure discharges along the entire drainage network and treatment facilities in order to reduce those water inflows. Several flow measurement devices were installed at strategic locations within the sewer network and integrated with a SCADA system responsible for its operation. A decision support system (DSS) is being implemented using the Delft-FEWS platform, integrating monitoring data and models. Based on monitored data and model results, an estimation of infiltration volumes during wet periods is presented. Moreover, the capabilities of the DSS are illustrated in: (i) location of manholes losses along sewer networks during wet periods; (ii) identification and location of unknown connections to the sewer network using wastewater balances; and (iii) design of a PID controller for a pumping station using on-line tank water level measurement. Acquired knowledge resulting from the DSS greatly improved the utility performance both in terms of economic revenue and environmental protection.

A systematic mixed-integer differential evolution approach for water network operational optimization

The operational management of potable water distribution networks presents a great challenge to water utilities, as reflected by the complex interplay of a wide range of multidimensional and nonlinear factors across the water value chain including the network physical structure and characteristics, operational requirements, water consumption profiles and the structure of energy tariffs. Nevertheless, both continuous and discrete actuation variables can be involved in governing the water network, which makes optimizing such networks a mixed-integer and highly constrained decision-making problem. As such, there is a need to situate the problem holistically, factoring in multidimensional considerations, with a goal of minimizing water operational costs. This paper, therefore, proposes a systematic optimization methodology for (near) real-time operation of water networks, where the operational strategy can be dynamically updated using a model-based predictive control scheme with little human intervention. The hydraulic model of the network of interest is thereby integrated and successively simulated with different trial strategies as part of the optimization process. A novel adapted mixed-integer differential evolution (DE) algorithm is particularly designed to deal with the discrete-continuous actuation variables involved in the network. Simulation results on a pilot water network confirm the effectiveness of the proposed methodology and the superiority of the proposed mixed-integer DE in comparison with genetic algorithms. It also suggests that 23.69% cost savings can be achieved compared with the water utility's current operational strategy, if adaptive pricing is adopted for all the pumping stations.

Performance evaluation of a smart buffer control at a wastewater treatment plant

Real time control (RTC) is increasingly seen as a viable method to optimise the functioning of wastewater systems. Model exercises and case studies reported in literature claim a positive impact of RTC based on results without uncertainty analysis and flawed evaluation periods. This paper describes two integrated RTC strategies at the wastewater treatment plant (WWTP) Eindhoven, the Netherlands, that aim to improve the use of the available tanks at the WWTP and storage in the contributing catchments to reduce the impact on the receiving water. For the first time it is demonstrated that a significant improvement can be achieved through the application of RTC in practice. The Storm Tank Control is evaluated based on measurements and reduces the number of storm water settling tank discharges by 44% and the discharged volume by an estimated 33%, decreasing dissolved oxygen depletion in the river. The Primary Clarifier Control is evaluated based on model simulations. The maximum event NH4 concentration in the effluent reduced on average 19% for large events, while the load reduced 20%. For all 31 events the reductions are 11 and 4% respectively. Reductions are significant taking uncertainties into account, while using representative evaluation periods.