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.

中文翻译：

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使用高级计量基础设施数据的水需求管理动态定价框架


本研究调查动态定价作为需求管理工具，通过减少高峰时段需求来降低成本并延长供水系统的使用寿命。使用高级计量基础设施 (AMI) 数据模拟个人消费者对每小时水价变化的反应。需求概况用作水力仿真模型的输入，以评估需求变化对流量和网络内指标的影响。该框架适用于加利福尼亚州莱克伍德市，使用管网模型和从近 20,000 个账户收集的 AMI 数据。该模型应用了四种动态定价政策，结果表明，早高峰需求减少 6% 至 25% 时，高峰能源需求最多可减少 14%。总体能源需求的这些微小变化（最多减少 1.7%）导致能源成本相对较大的总体下降（最多 5.5%）。结果证明了动态定价作为基础设施管理的需求方策略的重要性，并强调了在无需额外基础设施投资的情况下适应需求增长的潜力。