Urban wastewater sector is being pushed to optimize processes in order to reduce energy consumption without compromising its quality standards. Energy costs can represent a significant share of the global operational costs (between 50 and 60 ) in an intensive energy consumer. Pumping is the largest consumer of electrical energy in a wastewater treatment plant. Thus, the optimal control of pump units can help the utilities to decrease operational costs. This work describes an innovative predictive control policy for wastewater variable-frequency pumps that minimize electrical energy consumption, considering uncertainty forecasts for wastewater intake rate and information collected by sensors accessible through the Supervisory Control and Data Acquisition system. The proposed control method combines statistical learning (regression and predictive models) and deep reinforcement learning (Proximal Policy Optimization). The following main original contributions are produced: i) model-free and data-driven predictive control; ii) control philosophy focused on operating the tank with a variable wastewater set-point level; iii) use of supervised learning to generate synthetic data for pre-training the reinforcement learning policy, without the need to physically interact with the system. The results for a real case-study during 90 days show a 16.7 decrease in electrical energy consumption while still achieving a 97 reduction in the number of alarms (tank level above 7.2 meters) when compared with the current operating scenario (operating with a fixed set-point level). The numerical analysis showed that the proposed data-driven method is able to explore the trade-off between number of alarms and consumption minimization, offering different options to decision-makers.
The energy consumption across the globe is increasing at an alarming rate. This has already shown its impact in the depletion of energy sources and environmental issues (global warming, and weakening of the ozone layer). Certainly, this escalating tendency of energy insufficiency will get aggravated in the future. Efficiency enhancement initiatives are considered to be the key solution in reducing the energy utilization and eventually resisting the global environmental impacts. Of the world’s total energy generated, pumping systems, especially the centrifugal pumps consume about 20 . Consequently, the primary focus of global energy policy makers is to enhance energy efficiency in pumping systems. As per the literature, remarkable energy savings can be accomplished by controlling the speed of the pumping system using Variable Frequency Drives (VFDs). For this reason, studies and researches focus primarily on VFD control techniques to improve the efficiency of the pumping system. This article also focuses on component selection, and system dimensioning in addition to the control techniques. Comparison of recent research outcomes of energy efficiency improvements in pumping system has been made to provide an insight for future research.