As utilities continue to pump up their investments in smart grid technologies, this is creating rich opportunities for power companies to offer a wide variety of new applications and services to residential, commercial, and industrial customers.
For instance, revenue from smart grid distribution automation systems is expected to nearly double from $6.3 billion this year to $11.1 billion in 2020, according to a report from Navigant Research.
Distribution automation technologies can provide utilities the ability to sense and pinpoint faults in the electric grid, reroute power flows through “dynamic sectionalizing” and provide critical information to line crews to hasten repairs and recovery from power outages, according to the report.
By 2014, the global market for smart grid technologies and services will climb to tens of billions of dollars annually, according to a study by McKinsey & Co.
Meanwhile, the annual global revenue opportunity for residential customer applications is expected to range between $3 billion to $10 billion next year as in-home energy management tools such as programmable communicating thermostats enable customers to adjust their energy consumption to fit their usage patterns and spending preferences.
Despite the operational and business opportunities that abound from the continued build out of smart grids, many utilities find themselves at a disadvantage when it comes to mining and acting on the big data that’s being generated from these intelligent networks.
Many power utilities are hampered by their uses of outdated reporting and dashboard tools, according to a new report by BRIDGE Energy Group.
Most utilities (55%) continue to manage and access data through basic reporting and dashboards and aren’t able to analyze data beyond description, classification, and clustering, according to the study.
In fact, just 10% of respondents are leveraging progressive analytics trends and technologies such as data visualization techniques and real-time event streams that could provide them with rich insights on energy usage patterns.
These types of limitations also make it extremely difficult for power companies to act on real-time power consumption data generated by smart grids that can be used for supply/demand balancing and load forecasting to better anticipate and prevent costly outages.
Obsolete reporting and dashboard technologies also prevent utilities from discovering residential or commercial usage trends generated by smart grid data sets that might lead to new revenue opportunities.
For instance, the use of predictive analytics that’s blended with streaming smart grid data may inform utility executives that a high percentage of commercial customers in office buildings are wasting energy by leaving high-output lighting on overnight or by running heating or air conditioning systems inefficiently during non-peak hours.
Such insights could allow a power company to offer commercial customers revenue-generating energy management services that still manage to save clients money on power consumption.
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