Ironically, an industry long known as a technology laggard is now at the forefront of the Internet of Things (IoT) led by smart meters and other smart devices on the grid. And while utility customers have unprecedented access to their usage data, it does not even begin to rival the information being gathered by utilities. Sensors, monitors, controls and meters have transported utilities from the proverbial technological Stone Age straight into the middle of the big data era. Data analytics offer a gold mine of valuable insights, such as predicting equipment failures for preemptive repair or replacement, or eliminating redundancies to increase operational efficiencies. The million dollar question – how to maximize utilities’ data assets?
The potential analytics opportunities are enormous, but largely untapped to date. Those data assets that are literally growing by the minute can yield critical insights and opportunities in customer behavior analytics, asset analytics, and production analytics, among others. And within those insights lay the keys to improving service, efficiency, processes, and the utilities’ bottom line.
To be successful, utilities must innovate and find new insights to maximize efficiency and minimize spend, and they must act quickly. According to recent analysis by Bain & Company, in order to meet earnings growth targets without accelerating rate growth, North American utilities will need to cut some $15 billion—or roughly 20%—in operating and maintenance costs. To do that, utilities need to increase automation and leverage advanced technologies to streamline processes, reduce waste, and build an infrastructure scalable for the next hundred years.
The passage of the Energy Independence and Security Act of 2007 marked the official birth of the U.S. smart grid, with the federal government laying the groundwork through funding and policy for a coordinated effort to update an overtaxed and badly aging electric and energy infrastructure. It was at that point that, like it or not, all utilities were forced to confront a new reality.
In the decade since passage of that bill, the energy industry has undergone transformative change. From progress on the grid itself and a shift from analog devices to digital technologies, we’ve seen staggering progress with the adoption of intelligent devices, most notably the installation of smart meters in more than 50% of U.S. households as part of Advanced Metering Infrastructure (AMI) initiatives, enabling automated two-way communication of real-time data between utilities and customers. In addition, more than 1,200 Phasor Measurement Units (PMUs) have been installed for high-speed, real-time monitoring of grid stability. These are just two features in an evolving, complex ecosystem of control systems, telematics sensors, and devices networked to gather and process data in real time to automatically report outages, sense problems and re-route power as needed, and collect data on usage as never before.
It isn’t just the grid that’s changing, and it isn’t just electricity that’s affected. It used to be that utility customers were passive consumers in the truest sense of the word—they consumed electricity, water, and gas, and paid their monthly bills. Sometimes they might dispute a charge, sometimes they complained about rates, but for the most part they simply used their services and paid their bills. But today’s customers want to take a proactive role in managing their energy consumption, increasing efficiency, and controlling costs. They are environmentally conscious, and empowered to have a real impact through the products they buy and choices they make.
The utility sector helps enable these educated consumers with smart meters, which represent the industry’s most impactful foray to date into the Internet of Things (IoT). In addition to the electric smart meters previously mentioned, natural gas providers have also installed smart meters across the country to monitor and track gas consumption patterns. And while smart meter adoption is slower among water utilities due to high costs, with only about 20% of utilities reporting smart meter adoption, the benefits of obtaining real-time data about water usage, leakage, and quality are also readily apparent. Across all utilities, consumers are pairing the data from these meters with other intelligent devices to save both energy and money. This has resulted in weakened demand and lower prices, despite the need for utilities to continue to turn a profit. So what can utilities do?
As much as utilities would like to wave a wand and produce analytical insights, their big data repositories, filled to the brim with IoT data, likely needs some TLC. Whatever big data environment is in use, utilities must have an optimized data supply chain to handle the data ingested from thousands of systems and sources, much of it unstructured and of questionable quality. First, utilities need to validate and reconcile their data for consistency and accuracy. Next, the data must be centrally managed, and a framework of data governance must be put in place to ensure that the data can be trusted and mined for reliable insights. In effect, utilities and other data-rich organizations need a common data exchange to ingest, enrich and provision their data.
Finally, the data governance program needs to ensure that not only data, but the associated metadata is being managed in real time. Metadata is key to deriving true predictive analytics, which are critical to the insights and outcomes the utility sector badly needs. It is not enough to collect just data; data must be enriched with the physical, logical and conceptual metadata to take the sector into the next century.
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