Dynamic Pricing Framework for Water Demand Management Using Advanced Metering Infrastructure Data

Abstract This research investigates dynamic pricing as a demand management tool to reduce cost and increase the lifespan of water distribution systems by reducing peak hour demand. Individual consumer responses to changes in hourly water price are simulated using advanced metering infrastructure (AMI) data. Demand profiles are used as input to a hydraulic simulation model to evaluate the effects of changing demands on flows and in‐network metrics. The framework is applied to Lakewood City, California, using a model of the pipe network and AMI data collected at nearly 20,000 accounts. Four dynamic pricing policies are applied to the model to show that reductions in morning peak demand ranging from 6% to 25% reduce peak energy demands up to 14%. These small changes in overall energy demand, up to a 1.7% reduction, lead to relatively larger overall reductions in energy cost, up to 5.5%. The results demonstrate the importance of dynamic pricing as a demand‐side strategy for infrastructure management and highlight the potential to accommodate demand growth without additional infrastructure investments.