Impact of artificial intelligence in the reduction of electrical consumption in wastewater treatment plants: a review

Abstract

Wastewater Treatment Plants are energy-intensive consumers. Thus, understanding their energy consumption to achieve efficient management can provide considerable environmental and economic benefits. The complexity of the treatment systems, the non-linearity, and the uncertainty and data availability limitations require the use of energy audits, according to a truly holistic view, as well as the use of alternative analysis models and decision support, more efficient than traditional modeling techniques.   The purpose of this review paper is to identify practical examples of the main lines of thought using Artificial Intelligence algorithms used to reduce the consumption of electrical energy in the wastewater sector over the last years. From the several reviewed papers, from different research platforms, it is concluded that, despite the success of AI in reducing energy consumption, in particular Artificial Neural Networks, there is room to improve energy efficiency consumption, identifying or quantifying inefficiency phenomena associated with data collection.