Make better use of Real-Time Energy Information to improve service reliability
Improving the ROI of Real-time Energy Information
The business case for AMR has changed drastically over the years, generally toward better
Return on Investments (ROI) as AMR technologies evolve from monthly energy meter reads to
real-time energy information management (Benassi, 2001). In the past, the justification of AMR
mainly fell upon labor savings in meter reading for energy billing purposes. Today, the benefits
of enhancing customer services and competitive energy trading outweigh savings from labor
reduction. In addition to the fundamental energy consumption meter reading function, today’s
AMR lets the utility manage energy not only at the system level, but also at the customer level.
For example, for these advanced applications, it can provide:
-
Load profiling to help the utility work with Commercial and Industrial (C&I) customers to
devise energy management plans that are economically beneficial to both the utility and its
customers
- Improved design of automated feeder configuration to increase the utilization of existing
Transmission and Distribution (T&D) capacities with near real-time customer load data
- Controlled demands at the distribution and service level as an alternative resource to
traditional T&D expansion planning to improve capital utilization
- Enabled “dispatch” of customer loads and distributed generation resources as well as
generating plants to mitigate energy market risks
These advanced applications generally require AMR to use more robust and efficient data
communication that is on telephone lines or fixed wireless networks. Rather than discussing the
advancements and pros and cons of various AMR technologies, this paper focuses on the use of
the near real-time meter data to improve service reliability to further improve the ROI of today’s
AMR systems.
Focus on Service Reliability
Improving the energy delivery business requires a holistic view of the utility’s processes and
technology utilization, from customer service and dispatch operations to engineering and
planning (Tram, 1999). Hence, service reliability improvements involve two main areas: one on
remedial efforts of service restoration when outages occur and the other on efforts of planning
and engineering to prevent outage occurrences.
The first area of improvements relates to using real-time meter data to reduce the durations of
customer service interruptions and improve crew efficiency in the outage management process.
The improvements are possible by exploiting the metering information through the real-time data
network to:
- Improve the technique of trouble call and outage analysis to identify outage locations more
accurately and quickly;
- Lessen the effects of missing or erroneous customer and network connectivity data by
applying available real-time data on customer interruptions along with telemetries from
SCADA and geospatial information of customers;
- Increase the effectiveness of emergency load transfers by utilizing near real-time data of
customer demands along with circuit loadings and distributed generation for emergency
switching analysis; and
- Confirm service restorations promptly and without unnecessary nuisance to the customers
and without increased call-center or dispatching resources.
The second improvements area relates to using near real-time meter data for more effective asset
maintenance, engineering and planning to prevent network outages and reduce the service
interruptions for planned maintenance. The real-time data, and historical records of it, are useful
in these business processes:
- Formulating more cost-effective, value-based asset inspection and maintenance plans with
more accurate demand-based reliability analysis
- Increasing the effectiveness of transformer load management programs to prevent
transformer overload outages by estimating transformer loads more accurately
- Planning and managing maintenance outages more efficiently to reduce customer service
interruptions with near real-time customer demand information
- Facilitating system planning and engineering to reduce the frequency as well as duration of
customer interruptions by providing demand-based historical reliability data
The rest of the paper focuses on the first area of real-time data application to improve outage
management.
