Utilities are on board with the benefits analytics can bring. According to a 2018 BRIDGE Index Utility survey of some 20,000 north American utility workers, use of asset-related analytics rose 55% between 2016 and 2017, while grid-related analytics use rose 17% in the same period. In 2018,
There was a 42% increase in the number of utilities leveraging analytics technology.
Chances are, there’s growth ahead, too. Forty percent of survey respondents expected to spend between $1 and 6 million, while 13% put their 2018 analytics spend at $10 million or more. More than 60% said they were planning major analytics initiatives in the next two years.
According to the survey, two areas of utility operations get the most analytics attention: asset maintenance and outage management. Here is a look at a few of the ways that utilities are reaping analytics benefits.
Time-based or needs-based maintenance?
Some utilities take assets out of service and perform routine maintenance on a pre-determined schedule. Others are using analytics to determine when maintenance is performed. Salt River Project, a utility serving more than 2 million customers in central Arizona, for example, leverages analytics to determine when turbine generators need service and how to schedule that service without adversely impacting capacity.
The utility uses machine sensor data to precisely track generation uptime. This is because many manufacturers specify when maintenance should occur based on how much time the generation has been operating. Failure to service the generator before it has exceeded that specified run time can void a manufacturer’s warranty. SRP takes the guesswork out of that run-time calculation. That, in turn, helps the utility schedule asset maintenance without risking supply shortfalls, a pretty important thing in sizzling Phoenix, where temperatures top 100 degrees Fahrenheit an average of 110 days per year.
Low voltage, high load
The U.S. Department of Energy’s Voices of Experience (VOE) initiative brings utility staffers together to share ideas and insights gained from various utility activities, and then the DOE writes reports on the insights utility workers have shared. One utility that participated in VOE uses low-voltage data to find overloaded transformers.
Voltage drops when transformers are overloaded, so looking at low voltage enables utility managers to spot those over-taxed transformers before failure and, if necessary, redesign the neighborhood circuit. Voltage can also signal problems with regulation devices. “One utility had low voltage alarms on 300 meters allowing them to proactively replace the regulator before it failed,” noted the VOE report titled Leveraging AMI Networks and Data.
“Utilities are also monitoring voltage sags and swells to predict faulty or bad secondary wire connections,” the report authors continued. “Some are developing algorithms that include weather data because rain and lighting can cause damage to equipment that will present itself in the data.”
Researchers at Texas A&M University school of engineering created an intelligent model to identify vulnerability in utility assets and forecast where outages might occur. The model helps utilities prioritize tree-trimming activity after factoring in things like operational records and weather data as well as altitude and vegetation near utility service lines.
“The researchers describe their methodology for the framework as a three-part process,” explains a university news website. “First, they investigate the probability of a potential hazard, such as severe weather. Next, they assess the vulnerability of the utility assets by taking the weather probability and predicting its impact on the assets. The last and most significant step is evaluating the impact of certain events and the calculation of costs of reliability indices and maintenance, replacement and repair.”
Using the analytics model enables utilities to see vulnerable assets and schedule mitigation measures, thereby reducing outages and storm impacts.
Restoration & planning support
Utilities are using AMI data and analytic models to accurately map meters to transformers, a must-have element of effective outage communications as well as for determining whether a circuit can accommodate DER interconnection. “AMI data can be used to ensure meters are correctly mapped to the transformer they are connected to; an incorrectly mapped meter will have a different voltage from the other meters on that transformer,” notes the VOE report on Leveraging AMI Networks and Data. “Utilities can also use AMI data coupled with analytics to determine customer phase identification. Meter to transformer mapping, correct phase identification and mapping, and accurate GIS connectivity improve model accuracy and are crucial for capacity planning.”
One way to find energy diversion is to build models that compare consumption against predetermined thresholds or established patterns of usage. The model may include data related to customer class, business type, household size and other factors that impact normal usage. By tying the model into CIS data, the analytics can also factor in important data such as move-outs, foreclosures or vacation notifications. Then, when consumption significantly differ from anticipated usage, the model can trigger an alert that will signal the need for a site visit or other investigative action.
These are just a few examples of how utilities can leverage AMI data with analytics and boost the ROI of AMI investments as well as the efficiency of their operational activities. “Consultants with McKinsey have actually come up with an estimate about what the improved use of analytics can do for the financial results of a utility. Their finding: it can improve profitability by as much as 10 percent,” notes a recent playbook from Utility Dive.