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Water Resources Management

, Volume 33, Issue 2, pp 739–755 | Cite as

Pattern Detection and Scaling Laws of Daily Water Demand by SOM: an Application to the WDN of Naples, Italy

  • Roberta PadulanoEmail author
  • Giuseppe Del Giudice
Article
  • 61 Downloads

Abstract

In the present paper, a novel method is provided to detect significant daily consumption patterns and to obtain scaling laws to predict consumption patterns for groups of homogeneous users. The first issue relies on the use of Self-Organizing Map to gain insights about the initial assumption of distinct homogeneous consumption groups and to find additional clusters based on calendar dates. Non-dimensional pattern detection is performed on both residential and non-residential connections, with data provided by one-year measurements of a large-size smart water network placed in Naples (Italy). The second issue relies on the use of the variance function to explain the dependence of aggregated variance on the mean and on the number of aggregated users. Equations and related parameters’ values are provided to predict mean dimensional daily patterns and variation bands describing water consumption of a generic set of aggregated users.

Keywords

Pattern detection Scaling laws Self-organizing map Variance function Water demand patterns 

Notes

Acknowledgments

The Authors would like to thank ABC Acqua Bene Comune – Napoli, who installed the telemetry system and provided for consumption data.

Compliance with Ethical Standards

Conflict of interests

There is no conflict of interest.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Department of Civil, Architectural and Environmental EngineeringUniversità degli Studi di Napoli Federico IINaplesItaly

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