Philadelphia, Like Many Other Older Cities, has Benefited from Waves of Urban Renewal. Small commercial buildings and single-family residences have been converted to restaurants and apartment buildings. While PECO (Philadelphia, Pennsylvania, U.S.) takes an active role in the design and construction process to ensure adequate energy supply and delivery network, customers often embark on their conversion projects without notifying the utility. Such practices can lead to unexpected load growth on the distribution system. In some cases, the unchecked load growth stresses the distribution system and potentially leads to cable failures that may have a significant impact to the surrounding customers and facilities.

For example, during a recent 95°F (35°C) summer heat wave, the Old City historic area of Philadelphia experienced outages due to cable failures. While PECO immediately responded to restore service, PECO also initiated a capacity-expansion program to reinforce the electric distribution system in the area. The effort included the installation of new transformer banks and the replacement of underground cables. The casual load growth in this area had progressed unchecked and was attributed to be a cause of the failure.


PECO initially deployed its automatic meter reading (AMR) system in 1999 to provide more-accurate meter readings, reduce costs and improve customer satisfaction. PECO's AMR system provides meter reading services to 2.2 million electric and gas meters throughout Philadelphia and the surrounding counties. PECO has been continuously active in developing new applications to take advantage of the network and the data it generates. Initial successes have included an integration of its AMR, outage management systems and a revenue-protection program based on AMR data. This AMR-based Transformer Load Monitoring pilot is the newest application PECO is developing.


As part of PECO's ongoing effort to deliver reliable electric and gas service, the company has begun to develop programs that leverage the capabilities of the AMR system. In this case, PECO is piloting an application that monitors the electric distribution system in two thriving areas of Philadelphia's Center City — Old City and Chinatown.

Many utilities presently use monthly, daily or interval consumption data from check meters to identify high-growth or problem areas. The check meters are downloaded monthly. Load analysis then occurs as much as a month after the load occurs. By leveraging its AMR system, PECO is able to analyze these loads the day after they occur.

The analysis process includes developing an equipment load shape that is based on the input from as little as one check meter per transformer or cable device. The loads from the other devices are forecasted based upon the monthly data from the remaining meters that are served by the device in question.

PECO has taken this analysis technique one step further and extended the analysis to the 120/240-V secondary cables that directly serve the customer loads. The cables are part of the secondary service between the transformer and the electric meter. More specifically, they are either part of PECO's Center City secondary network or radial secondary mains that are express feeds from the transformer to the load pockets.

For this pilot, PECO summed the individual hourly meter readings for each transformer and secondary cable segment. This value represents the hourly demand for each device. A true 24/7 load shape can be created without the need for modeling or estimation. The data can then be used to develop weather sensitivities and emergency contingencies. The key to this type of analysis is a complete and accurate electric connectivity model.


To better leverage the AMR data for the purpose of studying distribution asset utilization, hourly interval data from the aforementioned areas of Philadelphia was imported into OSIsoft's (Hayward, California, U.S.) PI System. Each meter's data is represented within PI as a time stream of hourly data, ready for manipulation into more meaningful information. The Module Database within the PI System allows for a connectivity model to be developed so that the meter data can be grouped under a common secondary main or transformer.

Rather than building the connectivity model manually within PI, Excel spreadsheets containing the asset connectivity information were imported into the module database for automated creation of the data model. Ideally, future implementations would use a direct link from the source of record for asset connectivity to ensure that near-real-time analysis is accurately modeled.

With the asset model built, a means of aggregating the hourly interval data to the respective secondary main or transformer load was required. PI's Advanced Calculation Engine allowed for formulas to be stored against the secondary main or transformer asset to sum the interval data from their connected meters. These calculations are triggered so that new interval data imported for a meter will cause the calculation to run for its “parent” asset, thereby calculating the secondary main or transformer load to which it is connected.

Having a representation of the secondary main or transformer load is helpful, but upon analysis, it requires comparison to the rated capacity of the asset to allow for overload or load-duration studies. The asset model was expanded to allow for rating information on each asset. Transformer kilovolt-amp (kVA) ratings were readily available, and cable ratings were converted to a kVA rating representation in an attempt to compare them to an aggregate load value. This rating data was also loaded via a spreadsheet import into the module database.

Now that the data is in place, display of the data in an effective manner was required. The main two requirements for data analysis were the ability to identify assets that experienced short-term critical spikes in load and assets that experienced high cumulative load for a longer period of time. To this end, a custom display was developed in ProcessBook, which is PI's thick-client interface.


Due to the fundamental design of its AMR solution, PECO cannot activate interval data meter reading systemwide. With this limitation in mind, PECO is working to create a solution that uses the daily meter readings to get similar results. When a daily reading is used, the application then selects from a set of standard load shapes to closely approximate the daily load shape. Each customer's loads are adjusted according to the actual daily usage.

PECO has recently refreshed its standard rate-class load shapes to account for the evolving customer energy usage profiles. This effort was based on interval data gathered by PECO's AMR system

A pilot solution has been developed that will potentially extend the transformer loading analysis to all of PECO's distribution-class transformers. PECO is evaluating this opportunity to monitor the electric distribution system performance and to identify potential problems before they occur.

As AMI systems become more prolific across the nation, applications such as PECO's Transformer Load Monitoring system with cable management capabilities will become more standard and will lead to a dramatic change in how distribution systems are operated in the future.

Glenn A. Pritchard ( is a principal engineer on Exelon's Meter Reading Technology Team, where he specializes in finding new uses for PECO's AMR system and its data across multiple business units. Pritchard is currently leading PECO's AMI Technology Assessment Team. He has been with PECO for 18 years, and his experience ranges from distribution automation to reliability engineering. Pritchard holds a BSEE degree from Clemson University, and is a registered professional engineer in Pennsylvania and a member of the IEEE Power & Energy Society.

Lee Melville, a project engineer with Enspiria Solutions, leverages more than 12 years of experience in the electrical utility industry. He has a strong background in electrical engineering and network engineering and design, with experience across AMI, MDMS, substation automation, GIS, asset management systems and related technologies. Melville holds a BE degree in electronics and a ME degree in engineering management from University of Canterbury (New Zealand).