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.
More related with the work of the present paper, described a rule-based method to control WWTP pumps according to the measured wastewater tank level and minimize electrical energy consumption by using a fuzzy logic controller that work as follows: on rainy day's pumps react faster and frequency is increased quickly to avoid flooding; on dry day's pumps can react more slowly and frequency is decreased softly to prevent draining of the tank @cite_19 .
@cite_19
2122464586
In this study, first, designing and operating conditions of a wastewater treatment plant located in the south of Iskenderun of Hatay, Turkey, is examined and analyzed. It is shown that influent pumps have large part of energy consumption in plant. Second, some simulation and experimental studies were performed on plant. Energy efficiency and plant optimization have provided 40 of energy consumption. Also, experimental study is simulated by Matlab Fuzzy LogicController. The experimental results are in good agreement with the simulation results. © 2013 American Institute of Chemical Engineers Environ Prog, 33: 556–563, 2014