Abbotsford in British Colombia are installing analytics software and technology for smart water infrastructure.
The Canadian city has partnered with Innovyze to provide “accurate, customer-specific water usage patterns directly from AMIs for real-time modelling and management of Abbotsford water distribution system.”
The DemandAnalyst software will enable the City to import existing meter data and “automatically determine accurate, representative baseline demands and associated diurnal patterns for its comprehensive water distribution network model,” according to a statement.
In addition, Abbotsford can now continually update nodal demand values directly from its Advanced Metering Infrastructure (AMI) system to power decision making.
Addressing industry challenges
“Today, the water industry faces unique challenges. The need for water conservation, data accuracy and timeliness, operational efficiency and maintenance of distribution system hydraulic and water quality integrity has never been more pressing,” said Jeff Cowburn, Hydraulic Network Specialist for Abbotsford.
He continued that the new system provided the tools to effectively manage water distribution in real time, increasing resiliency and reducing inefficiencies.
Distribution modelling is an effective way of predicting system behaviour in order to address design, operational and water quality challenges. One of the most crucial is the ability to accurately predict daily water demand. This additional information thus enables utility personnel and planners to “optimise system operations and capital planning, improve conservation measures, minimize leakage and energy consumption, meet regulatory compliance and deliver superior customer service.”
Accurate water consumption modelling allows for customer specific (commercial, residential and industrial) load demand forecasts, and the ability to ensure supporting resources, distribution pipelines and available storage contribute to meeting these demands.
Most water utilities record water consumption data manually on a monthly, quarterly, half-yearly or yearly basis. This infrequent data collection is sufficient for billing purposes, but provides limited information on actual water consumption behavior, leakage, and seasonal variation — data needed for real-time network modeling.