Assessment of Smart-Meter-Enabled Dynamic Pricing at Utility and River Basin Scale

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of the marginal opportunity cost of water at weekly or longer timescales in the river basin from which water is withdrawn.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.

Consumption Change Detection for Urban Planning: Monitoring and Segmenting Water Customers During Drought

“…Recognition of the immense value of water conservation has led to a large body of literature devoted to studying the active strategies a utility can employ to induce savings behavior in its service area. Recent work has examined social norm‐based messaging (Ferraro & Miranda, ; Ferraro & Price, ), environment and health‐based feedback (Asensio & Delmas, ), rebates for water‐efficient retrofits (Schmitt et al, ), mandatory outdoor watering restrictions (Halich & Stephenson, ; Pratt, ; Wichman et al, ), block rate tariffs (Baerenklau et al, ), and dynamic pricing (Rougé et al, ), among others. There is growing evidence, however, that conservation behavior is also sensitive to external, climate‐related policy and mass media events that are beyond a utility's control.…”

Modelling Domestic Water Use in Metropolitan Areas Using Socio-Cognitive Agents

“…However, this requires large data sets of well-structured problems, which is not often the case for social phenomena (e.g., lack of data, unreliable data, and multiple models for different domains). Although machine learning can be useful for well-structured and recurrent problems which can be approached by statistical correlations (as urban demand evolution [52,53], dynamic pricing of water resources [54], prediction of daily peak demands, or prediction of network failures [55], this method may not be entirely suitable to explore possible future scenarios that represent disruptions from "business-as-usual" trends. Furthermore, recognising socio-ecological systems are complex, it is important to be aware of the assumptions and causal dynamics considered in the models [56].…”

Pricing Strategy for Residential Water in Drought Years. Application to the City of Tianjin, China

“…There have been studies paying attention to dynamic water pricing linked to the marginal benefit of water use. Rouge et al [20] provided an economic engineering conceptual framework for smart meter-enabled dynamic pricing of residential water. They linked water tariff design, across a range of timescales, to potential benefits at the utility and river basin scale.…”