How Total Cost of Ownership Can Help You Make the Right Meter-Reading Decision
By Todd Ellis
Water utilities need accurate data for a number of reasons. Frst and foremost, utilities need data from meters for billing. However, utilities also need meter data for other important purposes.
For example, utilities are continuously concerned about non-revenue water, which is water lost before it reaches customers through leaks, theft and inaccurate metering. Water utilities are encouraged by the American Water Works Association (AWWA) to audit for non-revenue water, but these audits are only as good as the data on which they are based. AMI provides the data foundation for accurate audits.
In addition, water customers are demanding better customer service and more information from utilities on how they are using water. Advanced metering infrastructure (AMI) technologies provide utilities with the data necessary to help customers manage their water use to save money and resources.
Yet, many utilities place more emphasis on the cost of meters rather than the long-term returns of collecting data from them. In fact, many utilities making decisions on how to collect data from meters rely on historic preferences as well the short-term capital costs related to acquiring and deploying meters.
To get an accurate picture of the total cost of ownership (TCO) of any system for collecting meter data, utilities should also consider the long-term capital and operating expenses related to their meter-reading solutions. These expenses vary considerably depending on the method used — whether manually by meter readers, by drive-by systems that wirelessly read devices from service vehicles, or via a fixed network that collects data automatically. As a result, evaluation of new systems needs to be based on a macro, longer-term view to assess the greatest return on investment and the potential for system and service improvements.
Water utilities looking to understand the true costs of a meter-reading system should evaluate the long-term expenses and benefits related to systems. A recent white paper by Aclara indicates that the choice of meter-reading network is a critical decision when determining the total costs of ownership related to reading meters over time.
Although the white paper focuses on electric utilities, many of its findings also apply to water utilities making decisions about what solutions to use for collecting meter readings.
Fixed, point-to-multipoint networks may offer the lowest TCO, the Aclara white paper found. TCO is financial estimate that considers both the direct and indirect costs of a product or system.
Major Cost Drivers
The Aclara white paper finds that capital costs and continuing operating expenses for both meters and the communications network are both important smart grid cost drivers for utilities. Capital costs for meter reading include meter replacement, AMI module installation and back-office software including the headend and meter data management. Continuing operating expenses for meter reading are determined by how the meters are read.
Capital costs affecting the communications network include meter-module costs, number of meters per data collector unit (DCU), installed costs per DCU, the costs of back-office software and hardware, number of meters per router, bridge (or repeater) and installed costs per router, repeater or bridge.
Factors influencing the ongoing operating expenses of the communications network are the number of meters read per month, the number of service orders handled per month, the cost of truck rolls, fully loaded average annual cost per communications network employee, automated meter-read success rate, automated service order success rate, meters per communications network employee, annual data backhaul cost per DCU per month, and annual software licensing and maintenance fees.
The Aclara Model
Aclara developed the model on which its white paper is based in conjunction with the Wired Group, a consultancy that reviewed and rendered an opinion on Aclara’s model based on its experience conducting comprehensive evaluations of smart grid deployments. The model encompasses the determinants described above and allows comparison of walk-by, drive-by, and fixed-network AMI. What Aclara found was that, over time, the highest costs relate to walk-by meter reading and the lowest related to advanced metering infrastructure.
The model takes into account the potential savings afforded to utilities that use fixed-network systems for implementation of time-varying rates, reduction of theft and non-revenue losses and deployment of prepayment programs (the first three factors are relevant also to water utilities, while prepayment programs are often used by electric utilities).
Basic data input to the model was verified through interviews with utilities. The model data can be changed in to more accurately reflect the utility’s individual case. The model is designed to predict TCO over a two-year deployment, followed by a 15-year project life span. The figure below illustrates a comparison using input collected during the model-validation process conducted by the Wired Group; capital and operational expenditures are compared.
Findings
Aclara found that if a utility chooses to manually read meters, then its operational costs continue to grow linearly over time. This is because the utility continues to experience costs related to transportation and personnel, not only for reading the meters but for rolling trucks for service calls.
Operational costs of drive-by networks are much lower than those related to manual meter reading, but over time those costs are somewhat higher than those of point-to-multipoint networks due to higher operating and maintenance costs.
When a utility chooses a point-to-multipoint solution over drive-by, ongoing operations and maintenance costs drop. In addition, point-to-multipoint networks provide the data necessary to improve consumer engagement and tackle non-revenue water issues. This effectively fulfills a utility’s business case to implement a more modern and efficient meter data collection method.
The model also indicated that there were also significant cost differences between point-to-multipoint networks and mesh networks. These are related specifically to higher capital and ongoing operating costs. Capital costs of mesh networks are higher due to requirements for additional networking equipment, while operating costs may be higher in part due to the need for more network engineering personnel to manage the communications network.
Point-to-Multipoint Network Benefits
The Aclara model suggests that point-to-multipoint networks provide lower TCO that other approaches including manual meter reading, drive-by solutions and mesh fixed networks, in part because they limit both upfront capital and ongoing operating costs. In addition, Aclara finds that the network architecture of point-to-multipoint fixed networks allows utilities to:
- Handle large numbers of meters communicating simultaneously without requiring capital expenditures to increase bandwidth;
- Support additional smart-infrastructure systems and non-meter distribution devices such as pressure sensors and overflow devices without needing additional hardware to increase bandwidth; and
- Capture data from hard-to-reach meters without using repeaters and range extenders to amplify signals.
Todd Ellis is a product manager at Aclara Technologies LLC, a supplier of smart infrastructure solutions to more than 780 water, gas and electric utilities globally. Aclara SIS offerings include smart meters and other field devices, advanced metering infrastructure and software and services that enable utilities to predict and respond to conditions, leverage their distribution networks effectively and engage with their customers.
