Studies and publications from the past ten years demonstrate that generally the energy efficiency of Waste Water Treatment Plants (WWTPs) is unsatisfactory. In this domain, efficient pump energy management can generate economic and environmental benefits. Although the availability of on-line sensors can provide high-frequency information about pump systems, at best, energy assessment is carried out a few times a year using aggregated data. Consequently, pump inefficiencies are normally detected late and the comprehension of pump system dynamics is often not satisfactory. In this paper, a data-driven methodology to support the daily energy decision-making is presented. This innovative approach, based on fuzzy logic, supports plant managers with detailed information about pump performance, and provides case-based suggestions to reduce the pump system energy consumption and extend pump life spans. A case study, performed on a WWTP in Germany, shows that it is possible to identify energy inefficiencies and case-based solutions to reduce the pump energy consumption by 18.5%.

过去十年的研究和出版物表明，废水处理厂（WWTP）的能源效率总体上不能令人满意。在这一领域，高效的泵能量管理可以产生经济和环境效益。尽管在线传感器的可用性可以提供有关泵系统的高频信息，但充其量，能源评估每年使用汇总数据进行几次。因此，泵的低效率通常会在很晚才被发现，并且对泵系统动力学的理解常常不能令人满意。本文提出了一种数据驱动的方法来支持日常能源决策。这种基于模糊逻辑的创新方法可为工厂经理提供有关泵性能的详细信息，并提供基于案例的建议，以减少泵系统的能耗并延长泵的使用寿命。在德国的一个污水处理厂进行的案例研究表明，可以发现能源效率低下和基于案例的解决方案，从而将泵的能耗降低18.5％。