Wastewater treatment plants (WWTPs) consume high amounts of energy which is mostly purchased from the grid. During the past years, many ongoing measures have taken place to analyze the possible solutions for both reducing the energy consumption and increasing the renewable energy production in the plants. This review contains all possible aspects which may assist to move towards energy neutrality in WWTPs. The sources of energy in wastewater were introduced and different indicators to express the energy consumption were discussed with examples of the operating WWTPs worldwide. Furthermore, the pathways for energy consumption reductions were reviewed including the operational strategies and the novel technological upgrades of the wastewater treatment processes. Then the methods of recovering the potential energy hidden in wastewater were described along with application of renewable energies in WWTPs. The available assessment methods, which may help in analyzing and comparing WWTPs in terms of energy and greenhouse gas emissions were introduced. Eventually, successful case studies on energy self-sufficiency of WWTPs were listed and the innovative projects in this area were presented.

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Achieving energy neutrality in wastewater treatment plants through energy savings and enhancing renewable energy production

Sustainable energy, water and food nexus systems: A focused review of decision-making tools for efficient resource management and governance

Model predictive control (MPC) can be used to manage combined urban drainage systems more efficiently for protection of human health and the environment, but examples of operational implementations are rare. This paper reviews more than 30 years of partly heterogeneous research on the topic. We propose a terminology for MPC of urban drainage systems and a hierarchical categorization where we emphasize four overall components: the “receding horizon principle”, the “optimization model”, the “optimization solver”, and the “internal MPC model”. Most of the reported optimization models share the trait of a multiobjective optimization based on a conceptual internal MPC model. However, there is a large variety of both convex and non-linear optimization models and optimization solvers as well as constructions of the internal MPC model. Furthermore, literature disagrees about the optimal length of the components in the receding horizon principle. The large number of MPC formulations and evaluation approach...

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Model predictive control of urban drainage systems: A review and perspective towards smart real-time water management

A novel energy assessment of urban wastewater treatment plants

Data-driven ecological performance evaluation for remanufacturing process

https://orbilu.uni.lu/bitstream/10993/37262/1/1-s2.0-S0306261917312928-main.pdf

A data-driven methodology to support pump performance analysis and energy efficiency optimization in Waste Water Treatment Plants

Energy saving in wastewater treatment plants: A plant-generic cooperative decision support system

Urban drainage modelling typically requires development of highly detailed simulators due to the nature of various underlying surface and drainage processes, which makes them computationally too expensive. Application of such simulators is still challenging in activities such as real-time control (RTC), uncertainty quantification analysis or model calibration in which numerous simulations are required. The focus of this paper is to present a rather simple hybrid surrogate modelling (or emulation) strategy to simplify and accelerate a detailed urban drainage simulator (UDS). The proposed surrogate modelling strategy includes: a) identification of the variables to be emulated; b) development of a simplified conceptual model in which every component contributing to the variables identified in step (a) is replaced by a function; c) definition of these functions, either based on knowledge about the mechanisms of the simulator, or based on the data produced by the simulator; and finally, d) validation of the results produced by the surrogate model in comparison with the original detailed simulator. Herein, a detailed InfoWorks ICM simulator was selected for surrogate modelling. The case study area was a small urban drainage network in Luxembourg. An emulator was developed to map the rainfall time series, as input, to a storage tank volume and combined sewer overflow (CSO) in the case study network. The results showed that the introduced strategy provides a reliable method to simplify the simulator and reduce its run time significantly. For the specific case study, the emulator was approximately 1300 times faster than the original detailed simulator. For quantification of the emulation error, an ensemble of 500 rainfall scenarios with 1 month duration was generated by application of a multivariate autoregressive model for conditional simulation of rainfall time series. The results produced by the emulator were compared to the ones produced by the simulator. Finally, as an indicator of the emulation error, distributions of Nash-Sutcliffe efficiency (NSE) between the emulator and simulator results for prediction of storage tank volume and CSO flow time series were presented.

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A Hybrid Surrogate Modelling Strategy for Simplification of Detailed Urban Drainage Simulators

In this paper, two types of controllers are proposed and compared to attain a better understanding of the potential of a real-time control (RTC) approach based on wastewater quantity and quality for combined sewer networks. The first controller is solely based on a wastewater quantity control approach, whilst, the second one is also considering wastewater quality modelling, as well as its uncertainty propagation. In fact, we have developed the first controller to achieve the second one without the requirement of adding new measurement devices to the given system. Model Predictive Control (MPC) approach is selected as the underlying control method. The control model in this study is a simple but fast model which is developed based on volume balance and mass balance laws in the tanks and time delay concept in the pipes. This model is described and applied to a simple case study to illustrate and discuss the results. The uncertainty propagation in the second controller is based on Taylor series of first order approximation. Based on the simulations and the achieved results, it was observed that the introduced pollution-based MPC approach is able to reduce significantly the volume of combined sewer overflows (CSOs) as well as the pollution load caused by them. Finally, it is concluded that considering the pollution load and its uncertainty propagation in the objective function of the optimization problem has a significant effect on the system performance improvement. This is a very important achievement because it can reduce the released pollution load to the environment without the requirement of additional equipment in the system. Because such elements (e.g. sensors) are normally expensive to purchase and maintain.

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Pollution-based Model Predictive Control Of Combined Sewer Networks, Considering Uncertainty Propagation

Waste Water Treatment Plants (WWTPs) are generally considered energy intensive. Substantial energy saving potentials have been identified by several authors. Pumps consume around 12% of the overall WWTP energy consumption. In this paper we propose a methodology that uses the sensors commonly installed in WWTPs, such as volume and energy sensors, to perform energy benchmarking on pumps. The relationship between energy efficiency and flow rate is used to detect specific problems, and potential solutions are proposed, taking into consideration economical and environmental criteria (cost of externalities in energy production). The methodology integrates energy benchmarking, data-mining, and economical and environmental assessment. In order to make better informed decisions, plant managers can now perform a multivariate analysis within a very short time, using information generally available in WWTPs.

Georges Schutz

Papers

A data-driven methodology to support pump performance analysis and energy efficiency optimization in Waste Water Treatment Plants

Energy saving in wastewater treatment plants: A plant-generic cooperative decision support system

A Hybrid Surrogate Modelling Strategy for Simplification of Detailed Urban Drainage Simulators

Pollution-based Model Predictive Control Of Combined Sewer Networks, Considering Uncertainty Propagation

A Tool for Energy Management and Cost Assessment of Pumps in Waste Water Treatment Plants