by Michael Price and Michael Cleveland, Deloitte Consulting LLP
Many advanced metering infrastructure (AMI) road maps properly and purposefully outline phased implementation strategies to align business processes with investment objectives, but utilities should consider meter hardware impacts early in the selection and design process. Potential technical and financial impacts might be realized based on these decisions. Although smaller, initial capital outlays for metering equipment might be attractive to a utility and regulator, there can be significant value in considering short- and long-term requirements to implement dynamic pricing and demand management capabilities.
The main choice a utility faces when selecting meter hardware is whether to purchase an index meter or load profile meter. In this case, only load profile meters are capable of measuring direct consumption. Both meter configurations provide the capability to implement flat-rate and basic time-of-use (TOU) billing. Only the load profile meter, however, will provide the capability to implement more advanced critical-peak pricing, peak-time rebate and real-time pricing billing tariffs.
These differences are important because technical impacts affect implementation costs. Index meters typically collect reads no more than a few times per day, thus field-area network traffic and backhaul requirements are relatively low. Because index-based consumption is calculated by subtracting latter reads from former reads, little register or channel configuration is required in AMI system components, and back-office configuration is relatively light because of flat-rate or basic TOU pricing structures. Field networks might require additional density propagation studies and equipment with a move to load profile meters because of increased network traffic, latency requirements and the potential to handle pricing signals to consumers. Incremental systems integration and application configuration will be required to create, manage and distribute complex rate tariff structures, baselines and validation, estimation and editing (VEE) processes when implementing demand management programs.
Although lower cost index meters might be attractive, such investments should be evaluated carefully against future-state functional road maps because several technical and business case implications exist when implementing more advanced critical-peak pricing, peak-time rebate and real-time pricing tariffs to support demand management programs. Although regulatory agencies may limit the amount of cost recovery associated with AMI and smart meter investments, initial procurement of index-only meters may result in incremental procurement, redeployment, systems and application configuration, and ancillary costs if a utility implements load profile meters later.
From a technical perspective, utilities might encounter moderate or significant impacts to assets on their AMI infrastructures if initial deployments primarily support index-only meters with one-or two-way communication capabilities. Beyond new meter procurement, utilities might need to address field-area network redesign efforts, backhaul bandwidth limitations and head-end meter data management system (MDMS) or customer information system (CIS) application reconfiguration.
Deloitte analyzed three technical configuration scenarios against five impact areas: metrology, AMI network, MDMS, middleware and CIS configuration. Technical configuration scenario one assumes the procurement of index meters to support flat-rate and basic TOU billing. Technical configuration scenario two assumes the procurement of load profile meters to support flat-rate and basic TOU billing. Technical configuration scenario three assumes the procurement of load profile meters to support advanced TOU billing and demand management capability.
Technical configuration scenario one (Figure 1), implementing flat or basic TOU billing via index meter configuration, is the least intrusive option. Index meter costs are lower than load profile meter costs. AMI networks need only handle limited reads and no events or alarms. MDMS configuration for physical channels, rates, storage capacity and validation is minimal. Middleware configuration is relatively light because of limited interfaces. In addtion, CIS invoicing and bill print processes are simplified.
Technical configuration scenario two (Figure 2), initial deployments of load profile meters configured for index reads, adds only marginal costs to meter procurement and asset configuration costs compared with the first scenario. Depending upon the utility’s decision to collect interval data, meter events and alarms, and other network data requirements while still billing usage from index reads, AMI network costs could vary based on latency, topology and interrogation volumes. MDMS configuration costs vary depending on whether interval data is in play and setting up VEE. Middleware costs could be impacted because of the potential for multiple format translations if multiple AMI headends are employed. Yet, compared to the previous scenario, CIS configuration costs are likely similar because index billing is consistent.
Technical configuration scenario three (Figure 3) assumes full deployment of load profile meters and associated interval billing. In general, costs are considerably higher because of additional field devices to handle increased network traffic; multiple interfaces to upstream and downstream systems such as the outage management system (OMS); physical and logical channel management and VEE configuration in meters and the MDMS; and complex rate program management within the CIS.
Deloitte explored two transition scenarios and associated technical impacts. Transition scenario one considered an initial deployment of index-only meters and flat-rate or basic TOU billing against a secondary deployment of load profile meters to implement the same billing scheme. This approach requires a mass meter exchange, network propagation studies, additional moderate systems integration and configuration to headends, MDMS and back-office applications. The utility’s cost for these changes is significant. The additional interval data could result in bandwidth issues and AMI network re-optimization issues. The MDMS likely would be impacted further because of additional data storage requirements and VEE configuration. The middleware likely would be impacted by the need to translate additional interval data between the headend and MDMS. The CIS likely would be impacted to account for additional meter device register configuration.
Transition scenario two considered an initial deployment of load profile meters configured to support a flat-rate or basic TOU billing program against the implementation of advanced pricing tariffs. While the initial technical impacts to implement load profile meters are significant, incremental hardware and network costs are insignificant. Cost impacts are limited generally to MDMS and CIS configurations to support additional VEE, framing, complex billing, invoicing and bill print. Redeployment costs of new meters are mitigated in this scenario. The AMI network, MDMS and middleware infrastructure already would have been built to handle higher-volume interval data. This is a much smaller project compared with transitioning from index to load profile meters.
There are technical impacts as demonstrated in these program transition scenarios. These technical impacts can directly drive cost and turn an initial, positive business case negative when implementing advanced billing and demand management processes. This is demonstrated further in the following three investment scenarios.
In the first investment scenario, utilities may invest in index meters because of regulatory mandates, current state business drivers or constrained funding. The business case is often positive because of low capital investment and corollary costs. This assumes the technology and customer programs are sufficient per the business drivers. Although this option might seem frugal up front, the utility likely will implement advanced TOU billing later, which will yield scalability issues. Utilities in this situation likely will experience duplicative and higher costs associated with meter acquisition, meter deployment and supporting infrastructure, in addition to stranded asset costs. Even considering the benefits of demand management and dynamic pricing, this approach can result in a negative overall business case. Utilities should, therefore, approach these investment decisions with a long-term view and consider the configuration options holistically.
Many utilities prepare for the future but do not necessarily invest aggressively up front. In the second investment scenario, a utility may invest in meters with load profile configurations capable of advanced TOU billing but only implement flat-rate and basic TOU billing to save on the other costs and follow a prescribed deployment strategy. This strategy enables the utility to implement advanced TOU billing when required with less financial strain. This typically results in a positive business case up front; however, the utility can experience a longer time to break even on the investment because advanced TOU billing is not implemented initially. Looking at the business case, the utility will invest more up front compared with investment scenario one—the primary cost differential’s being the load profile meter itself. Taking this anticipatory approach will not incur the duplicative costs for meter acquisition and meter deployment; however, the utility still might need to reinvest in supporting infrastructure, system integration and corollary expenses to enable advanced pricing tariffs.
If a utility invests up front in load profile meters and supporting assets to enable advanced TOU billing in the third investment scenario, initial investments can be higher than illustrated. Nevertheless, utilities that implement advanced TOU billing up front can realize benefits more rapidly. Despite an initially higher investment, the business case still has the potential to be positive long term by considering scalability and mitigating against external drivers that could force reinvestments in meter acquisition, meter deployment, infrastructure, system integration and corollary expenses. Although this article focuses on the capital outlays to support the alternative scenarios, utilities should factor in total cost of ownership, including operational expenditures.
Utilities that acknowledge evolving smart grid technologies, regulatory mandates, business drivers and consumer pricing trends over a longer horizon likely will make more informed investment decisions that take technology and business scalability into consideration from the beginning and forecast drivers that might yield technical and cost impacts.
For more information or to review the unabridged whitepaper, visit the Deloitte Center for Energy Solutions, http://deloitte.com/us/dynamicpricing.
Michael Price is a specialist leader and Michael Cleveland is a manager with Deloitte Consulting LLP. Both provide guidance to power and utility clients as smart grid subject matter leaders in addition to supporting and developing Deloitte’s smart metering and smart grid presence globally. Reach them at email@example.com and firstname.lastname@example.org.
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