Innovation ARIMA models application to predict pressure variations in water supply networks with open-loop control. Case study in Noja (Cantabria, Spain)

TL;DR

This study applies ARIMA models to predict pressure variations in water supply networks with open-loop control, aiming to improve anomaly detection and pressure management using real data from Noja, Spain.

Contribution

It introduces a novel application of ARIMA models for pressure prediction in water networks, enhancing anomaly detection and operational efficiency.

Findings

ARIMA models accurately forecast pressure variations.

Enhanced detection of abnormal pressure patterns.

Improved pressure management in water networks.

Abstract

Water utilities are increasingly concerned about losses, leaks, and illegal connections in their distribution networks. Pressure control is typically managed through pressure reducing valves with electrically controlled actuators based on predefined tables according to the pressure at the critical point control. This openloop control method lacks direct feedback between the PRV and CPC, making it challenging to distinguish whether pressure variations originate from normal head losses or abnormal network conditions. Unlike traditional applications of ARIMA focused on water demand forecasting, this study explores its novel use in pressure management within distribution networks, aiming to predict P3 pressure based on head losses across a defined hydraulic sector. To achieve this objective, a predictive model based on the Box-Jenkins methodology and its variations is implemented to analyse time series data. An action path is established to determine the optimal model ARIMA, ARMA, ARMAX, etc. which is subsequently validated using real operational data from Noja, a coastal town in northern Spain characterized by significant seasonal population fluctuations. By accurately forecasting CPC pressure, this system enhances the detection of anomalous patterns, enabling more efficient network pressure management. The study demonstrates the potential of advanced modelling techniques in optimizing water distribution networks, providing valuable insights to improve system efficiency, reliability, and sustainability in urban environments.