Abstract

The advent of smart metering is set to revolutionize many aspects of the relationship between water utilities and their customers, and this includes the possibility of using time-varying water prices as a demand management strategy. These dynamic tariffs could promote water use efficiency by reflecting the variations of water demand, availability, and delivery costs over time. This paper relates the potential benefits of dynamic water tariffs, at the utility and basin scale, to their design across a range of timescales. On one end of the spectrum, subdaily peak pricing shifts use away from peak hours to lower a utility’s operational and capital expenses. On the other end, scarcity pricing factors in the variations of the marginal opportunity cost of water at weekly or longer timescales in the river basin from which water is withdrawn. Dynamic pricing schemes that act across timescales can be devised to yield both types of benefits. The analysis estimates these benefits separately for Greater London (United Kingdom) and its 15 million inhabitants. Scarcity pricing implemented on a weekly timescale equates the marginal cost of residential water with estimates of the marginal economic values of environmental-recreational flows derived from tourism, property values, etc. Scarcity pricing during droughts could result in a 22–63% average reduction in environmental flow shortage while residential price increases would be capped at 150% of base levels. Yet, its ability to protect environmental flows could decrease in extreme shortage situations. The net present value of savings from peak pricing is conservatively evaluated at approximately £10 million for each initial percentage point in daily peak-hour price increase.

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Data Availability Statement

Data and code generated by the authors or analyzed during the study are available at https://github.com/charlesrouge/Dynamic_Pricing.

Acknowledgments

The work was supported by the research project “SmartH2O: an ICT Platform to leverage on Social Computing for the efficient management of Water Consumption,” funded by the EU Seventh Framework Programme under Grant Agreement No. 619172, and by EPSRC Grant No. EP/G060460/1. The authors wish to thank Anna Wallen for comments on this manuscript, as well as the editor, associate editor David Rosenberg, and three anonymous reviewers, for their constructive comments.

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Information & Authors

Information

Published In

Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 144Issue 5May 2018

History

Received: Nov 15, 2016
Accepted: Aug 11, 2017
Published online: Mar 8, 2018
Published in print: May 1, 2018
Discussion open until: Aug 8, 2018

Authors

Affiliations

Research Associate, School of Mechanical, Aerospace and Civil Engineering, Univ. of Manchester, Manchester M13 9PL, U.K. (corresponding author). ORCID: https://orcid.org/0000-0003-1374-4992. E-mail: [email protected]
Julien J. Harou [email protected]
Professor, School of Mechanical, Aerospace and Civil Engineering, Univ. of Manchester, Manchester M13 9PL, U.K. E-mail: [email protected]
Manuel Pulido-Velazquez [email protected]
Professor, Research Institute of Water and Environmental Engineering, Universitat Politècnica de València, Camí de Vera s/n, 46022 Valencia, Spain. E-mail: [email protected]
Evgenii S. Matrosov [email protected]
Research Fellow, School of Mechanical, Aerospace and Civil Engineering, Univ. of Manchester, Manchester M13 9PL, U.K. E-mail: [email protected]
Paola Garrone [email protected]
Professor, Dept. of Management, Economics and Industrial Engineering, Politecnico di Milano, Via Lambruschini 4/b, 20156 Milano, Italy. E-mail: [email protected]
Riccardo Marzano [email protected]
Postdoctoral Researcher, Dept. of Management, Economics and Industrial Engineering, Politecnico di Milano, Via Lambruschini 4/b, 20156 Milano, Italy. E-mail: [email protected]
Antonio Lopez-Nicolas [email protected]
Ph.D. Researcher, Research Institute of Water and Environmental Engineering, Universitat Politècnica de València, Camí de Vera s/n, 46022 Valencia, Spain. E-mail: [email protected]
Andrea Castelletti [email protected]
Associate Professor, Dept. of Electronics, Information, and Bioengineering, Politecnico di Milano, P.za Leonardo da Vinci, 32, 20133 Milano, Italy. E-mail: [email protected]
Andrea-Emilio Rizzoli [email protected]
Professor, Dalle Molle Institute for Artificial Intelligence Research, Università della Svizzera Italiana/Scuola Universitaria Professionale della Svizzera Italiana, 6928 Manno, Switzerland. E-mail: [email protected]

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