Managing Utility Assets with the Power of your Data

Companies in water / wastewater treatment, distribution and collection want to more effectively integrate and analyze real-time and historical data with existing systems, automation and controls for more sustainable, profitable operations.

Utilities invest considerable sums of money in their water and wastewater networks - so it is probably worth spending a little more to ensure they operate efficiently. As the vital importance of water conservation grows ever more apparent, large amounts (of water and money) can be saved simply through rapid detection of leaks and other untoward events on a water network's pipelines. The water industry has been slow to take advantage of information technology, but it is catching up quickly. In many parts of the world, water managers now depend entirely on real-time data to manage their water supply and wastewater services. Automation has become a core enabler of the operations.

Water loss due to leakages is a bigger problem than people may think. With regard to water leakage in India, this is of major concern and of significant importance to those companies involved in the transportation of water any leakage can have significant financial consequences.

In India there is great opportunity and benefit to manage leakage considering the scarcity and cost of drinking water in the region coupled with unreliable weather prediction and truant monsoons. It is gradually being accepted that Water networks need to be managed and maintained around the clock and, as a result, the concept of infrastructure asset management,

Conventional methods of leak detection rely mainly on the expertise of operators to identify leaks within the system based on pressure losses at various locations. Pressure management and DMAs (district metered areas) are used to prevent leaks and detection is typically done by using acoustic listening devices, leak noise correlators and tethered hydrophone systems

Although this method works in the case of large leaks in which there is a considerable loss of pressure in the pipeline, it is more difficult to identify smaller leaks which, over time, cause a majority of the total water lost. Leaks that are not visible in the water distribution system can go undetected for months and even years. Typically water leaks don't happen quickly - they appear over a period of time.


The challenge is not only to detect, but even avoid a water leak in the first place. Data acquisition software allows a utility to collect data from all control systems and instrumentation, which is the key to water leakage prevention and detection. Without the data, a utility can only guess at the amount of leakage and would not be able to detect long run leaks that are not visible.

Utilities need to be able to collect and analyse data before any optimisation or leakage reduction can be accomplished and measured. Based on the constant stream of data collected from water meters, the system can conduct real-time water balances to alert operators of possible leaks or anomalies in the entire water distribution network. It can reconcile the entire water distribution system in real-time.

A software-based leak detection system will assist the operators of the pipeline to quickly and accurately identify potential and actual leaks and put into place measures to reduce the losses.

In an attempt to overcome some of the telemetry issues which generally face these systems, solutions have been developed which can provide leak detection analysis based on data received on an hourly basis, performing analysis runs of the hourly data within minutes to determine the status of the pipeline.

Real-time data describing various pumping scenarios is brought into the system and analyzed via performance equations to give required summary information (e.g., daily totals, averages). The system is configured to perform a range of analyses automatically with real-time and historical data, such as: comparisons conducted between seasonal periods; and overlaying similar months from a number of different years and contrasting aggregates over two- to five-year periods.

Modern analytic tools provide the ability to embed analysis and models automatically, as opposed to manually combing data from disparate systems, resulting in predictive information that gives insight into the capability of the infrastructure to meet operational demands.

In the future, users can plan to take this a step further, to add system capabilities that proactively notify users - a big step, which will eliminate the requirement for constant monitoring.

Demystifying the Enterprise Data Historian

An enterprise data historian is a central data repository for all process control information in your enterprise, encompassing all real-time and historical information (time series) collected from automation and control systems. A valuable tool for utilities, data historians turn raw process control data into actionable, consistent information, leading to improved decision making and efficient operations.


Control and automation systems can generate volumes of data - from sub-second to only on an exception-basis - but companies don't know how much data is going to be generated (e.g.. number of values and changes in values); therefore, they cannot effectively collect all the information in relational databases.

The data historian, based on a time-series database (non-relational), allows users to collect all the relevant information they need and analyze it based on raw and aggregated values. Time-series process control data can then be leveraged with other existing enterprise or business systems, such as: ERP, CMMS, GIS mapping, LIMS or asset management.

- Abraham Samson