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Enhanced Demand Forecasting and Leakage Detection using High-Resolution Loggers

This project aims to develop improved demand forecasts and leakage detection utilizing high-resolution data. Objectives include analyzing the data, understanding demand factors, predicting consumption levels, and extrapolating forecasts. The project involves the use of pulse loggers and aims to address water scarcity and stress conditions.

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Enhanced Demand Forecasting and Leakage Detection using High-Resolution Loggers

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  1. Enhanced demand forecasting and leakage detection utilising high-resolution loggers Centre for Water Systems University of Exeter PhD Student: Paul Wills Principal Supervisor: Fayyaz Memon Second Supervisor: Dragan Savic Industry Partner: South West Water

  2. The overall aim is to develop improved demand forecasts and leakage detection using high resolution data. The key objectives include to: • Determine the best techniques for analysing this new high-resolution data • Understand the factors involved in demand/consumption and their magnitude • Predict demand/consumption levels based on given factor inputs (e.g. behaviour profiles, weather data, tourism data, seasonality, diurnal/nocturnal patterns) • Utilise the demand predictions to determine possible leakage • Compare leakage detection results with the night-flow analysis • Extrapolate consumption forecasting to areas without high-resolution loggers • Agglomerate forecasts to make predictions on a District-Metered-Area (DMA) level www.wisecdt.org

  3. The novelty in this project comes through using high-resolution loggers, particularly the pulse loggers (Figure 1). “ By 2025, 1.8 billion people will be living in countries or regions with absolute water scarcity, and two-thirds of the world population could be under conditions of water stress. ”(UN-Water 2007) Figure 1. Pulse data logger with 1L pulse resolution capability. (Ashridge Engineering 2017) www.wisecdt.org

  4. Figure 2. Spreadsheet of recorded pulse data www.wisecdt.org

  5. Timeline: • Stage 1 – 4 months – Literature review, design, experimentation. • Publication 1 – Literature review • Stage 2 – 6 months – Initial demand model construction • Stage 3 – 2 months – Utilisation / testing of demand model with full datasets. • Stage 4 – 4 months – Refinement of demand model, increasing accuracy • Publication 2 – Demand modelling • Stage 5 – 6 months – Extension of model to predict leakage • Stage 6 – 2 months – Testing of extended model • Stage 7 – 2 months – Refinement of extended model, improving performance • Publication 3 – Leakage detection • Stage 8 – 4 months – Extrapolation – prediction for other types of meter • Publication 4 – Extrapolation performance • Stage 9 – 6 months Overlap / Extension / Writing up • Stage 10 – Thesis submission www.wisecdt.org

  6. References: Ashridge Engineering, (2017). Data-logger-2017 [ONLINE]. Available at: http://www.ash-eng.com/wp-content/uploads/2017/05/Data-logger-2017-140x124.png [Accessed 15 June 2017]. UN-Water (2007). Coping with Water Scarcity: Challenge of the Twenty-First Century. United Nations, New York. www.wisecdt.org

  7. Any questions? For more information contact: pw375@exeter.ac.uk www.wisecdt.org

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