H33O-08
Modeling and managing urban water demand through smart meters: Benefits and challenges from current research and emerging trends

Wednesday, 16 December 2015: 15:25
3002 (Moscone West)
Andrea Cominola1, Matteo Giuliani2, Andrea Castelletti1, Dario Piga3 and Andrea Emilio Rizzoli4, (1)Politecnico di Milano, Milano, 20133, Italy, (2)Politecnico di Milano, Milano, Italy, (3)IMT Institute for Advanced Studies Lucca, Lucca, Italy, (4)The Dalle Molle Institute for Artificial Intelligence Research, Lugano, Switzerland
Abstract:
Urban population growth, climate and land use change are expected to boost residential water demand in urban contexts in the next decades. In such a context, developing suitable demand-side management strategies is essential to meet future water demands, pursue water savings, and reduce the costs for water utilities. Yet, the effectiveness of water demand management strategies (WDMS) relies on our understanding of water consumers’ behavior, their consumption habits, and the water use drivers. While low spatial and temporal resolution water consumption data, as traditionally gathered for billing purposes, hardly support this understanding, the advent of high-resolution, smart metering technologies allowed for quasi real-time monitoring water consumption at the single household level. This, in turn, is advancing our ability in characterizing consumers’ behavior, modeling, and designing user-oriented residential water demand management strategies.

Several water smart metering programs have been rolled-out in the last two decades worldwide, addressing one or more of the following water demand management phases: (i) data gathering, (ii) water end-uses characterization, (iii) user modeling, (iv) design and implementation of personalized WDMS. Moreover, the number of research studies in this domain is quickly increasing and big economic investments are currently being devoted worldwide to smart metering programs. With this work, we contribute the first comprehensive review of more than 100 experiences in the field of residential water demand modeling and management, and we propose a general framework for their classification. We revise consolidated practices, identify emerging trends and highlight the challenges and opportunities for future developments given by the use of smart meters advancing residential water demand management.

Our analysis of the status quo of smart urban water demand management research and market constitutes a structured collection of information supporting the development of integrated procedures in the field of urban water management, as well as common actions aiding the collaboration with other sectors, as the nexus with energy demand management.