Water utilities are facing the threat of aging infrastructure, increasing costs and decreasing revenue. Factor in the uncertainty associated with increased volatility in the hydrologic cycle and it can be easy to understand the extreme financial and operational pressures these utilities encounter. Fortunately for today’s utilities, tools including data-driven systems and processes that drive efficiency into utility operations are generating opportunities to rein in these problems, providing the platform to achieve financial and operational sustainability.
One of the key benefits of advances in data-driven systems for utilities is the availability of near-real time information.
On the metering front, these systems bring the tools of demand-side management (DSM) and comparative behavioral science to utilities. When combined, they reduce overall water consumption while ensuring the collectability of all available revenue.
In contrast to supply-side water management—which places emphasis on generating new water through increased diversions, massive engineering works or potable water creation schemes such as desalination—DSM allows utilities to maximize the efficient use of water. To be successful, however, any DSM program must be supported by a robust revenue assurance program accounting for every drop produced and sold, and eliminate non-revenue water and leaks. Addressing the “revenue destruction” aspects of DSM head-on is critical. This is why starting with the meter-to-customer process is so powerful. The benefits accrue immediately to utility operations and customers while preserving revenue.
By providing real-time consumption information to customers, utilities can realize significant water savings, which can translate into the deferral of infrastructure construction and water acquisition costs. In some utilities, through the application of data-driven DSM, per capita demand has been reduced an average of 10 percent, simply by re-connecting customers to their water use in near real time, and giving people context for their consumption by offering comparisons of their use to their neighbors, their community and their city.
What does this demand reduction mean for utility operations? First, it means a direct reduction of the utility’s power requirements. Second, it means the fitted infrastructure can be extended to serve more people. It also means that utilities can begin to employ management techniques to provide active pressure control, which in turn further reduces power costs, non-revenue water and main breaks. In short, data-driven DSM sets the stage for financial and infrastructure sustainability for utilities.
As a first order approximation, the power required to supply water is a function of flow, pressure, the fluid’s specific gravity, and pump and motor efficiency. From a utility perspective, while there may be some control over the pump and motor efficiency by designing and operating systems on the pump curve, the impacts of reducing pressure or flow can be more impactful.
By reducing demand, utilities can realize three immediate benefits:
- Operating pressure can be reduced. A 10 percent reduction in flow reduces the pressure requirements by 19 percent. Reducing the overall demand reduces the pressure necessary to move water through the distribution system. And as pressure is proportional to the square of the flow (velocity), the effects are compounded for pressure.
- Line losses, typically directly proportional to velocity (flow), are decreased, further reducing the pressure requirements.
- The physical strain on aging infrastructure can be reduced.
These reductions in pressure combined with data-driven DSM can result in large power savings. For example, reducing demand from 210 gallons per capita per day (GPCD) to 175 GPCD, and pressure from 75 pounds per square inch (psi) to 65 psi can reduce the distribution system and power requirements by nearly 1.0 kilowatt-hours per dwelling unit per day (kWh/DU/day). With an average power cost of $0.09/kWh, the resultant savings are more than $1 million per year in a 100,000-home community.
An oft-overlooked benefit of employing these management systems is “found capacity.” As a result of data-driven DSM activities, capacity liberated from existing systems.
Because water infrastructure typically scales linearly with population,1 demand reductions can be translated into direct availability for new consumers and into significant deferral—or even elimination—of near- and long-term capital projects.
As an example, a typical capacity calculation for utility infrastructure includes average daily flow, a peaking factor assessment, an allowance for leakage and an allowance for fire flow. By reducing overall consumption, both the peak hour flow and maximum daily flow are reduced by an equivalent amount, allowing infrastructure elements like pump stations to serve more homes.
Since water storage requirements are often based on the “average day maximum month” flow plus an allowance for fire flow, a reduction in demand translates to a reduction in the storage requirements for the existing population, and by extension creates storage capacity in the existing infrastructure for future use.