Propagation modeling provides pinpoint accuracy for meter collection system planning
As municipal budgets and utility staffing continue to decrease across the U.S., the need to account for every drop of customer water usage is paramount to obtain all available billing revenues. As a result, meter reads and data collection systems are perhaps the most crucial components of any utility management operation.
Fixed-based systems are gaining in popularity because of their cost-effective, highly accurate and frequently accessible data collection capabilities. However, don’t be fooled into thinking that fixed-based equipment will cause accuracy rates to soar.
Rather, the most important element to implementing a successful fixed-based program is pinpointing the most effective placement of the data collection devices, which detect, process and forward messages transmitted by the AMR modules of individual meters.
Thanks to the methodology behind propagation modeling, utility companies can deploy these systems with hard data to back up their choices. Propagation modeling is proving to be a superior approach to the traditional sq-mile analysis as the road map for determining where and how many structures are needed in any given geographical area.
Propagation models analyze data such as desired coverage area, performance goals, terrain, growth expectations and existing utility-owned infrastructure throughout a given area. This information can be used to find potential collection sites in order to determine the optimal amount and locations of equipment.
By using propagation modeling as the core of the planning process, utility officials can uncover the most efficient planning available to minimize costs and meet performance expectations.
First things first
Before a utility can start a propagation study, it must produce a clear set of infrastructure assets as well as its growth potential and goals. Using utility-owned sites is the key element in providing an economical fixed-based deployment because it minimizes the need for leasing and/or equipment sharing with other utilities or publicly owned structures, which saves time and money.
Critical questions to address in the information-collecting stage include: meter locations (inside/outside, above or below ground, etc.); territory boundaries; future growth plans; utility-owned sites that may host collection devices; and the heights and locations of those sites.
“This up-front work is crucial to give the vendor enough critical information to complete the modeling process,” said Tim Harriger, director of marketing, Sensus Metering Systems. “Identifying this information is also beneficial to the utility because they will then have a complete understanding of the process and how it will ultimately help in meeting the organization’s performance goals.”
Harriger added that the vendor should be fully aware of the utility deployment strategy in order to effectively propose a system that meets those requirements.
Once the two sides have a complete understanding of the utility deployment strategy, a proposal is created to identify system requirements and coverage.
Creating the deployment plan
Prior to the use of propagation modeling proposals, utilities were relegated to defining system requirements using a “cookie-cutter” method. Collectors are placed along a pre-determined grid based strictly on square miles and a mathematical equation, regardless of the environment and meter population. This application maximizes system requirements and adds to the overall cost of installing and maintaining a fixed-based system.
Problems abound with this method. Without qualifying preliminary infrastructure sites, the utility may encounter obstacles during deployment, such as inadequate facilities and property rights and/or leasing issues. Also, the sheer number of sites stresses a utility’s manpower for maintenance and repair issues, which impacts the system’s life costs and could make a system deployment difficult to justify financially.
Conversely, propagation modeling provides a thorough and accurate assessment through detailed analysis. Utility information is fed into modeling software, and the area is plotted to uncover terrain characteristics. Propagation modeling is an above-the-grid method because utilities have their own set of assets, liabilities and terrain factors that ultimately affect the final proposal.
Once the territory is plotted, the proposed data collector sites are added to the model, and the analysis begins on which sites will achieve the most efficient coverage of the area. Often, the number of proposed sites exceeds the number of hosts needed. Typically, the model returns recommendations for fewer collector devices than utility officials anticipated, which is the first cost-saving measure in the process.
“Without the results of propagation modeling to design an implementation plan, deploying a fixed-based system is subject to random use of equipment, which could mean higher infrastructure requirements and higher operational and maintenance costs than necessary,” Harriger said. “Simply put, propagation modeling eliminates guessing.”