As power utility organizations invest in an increasing array of ‘smart’ technologies to improve operations and give customers more oversight of their power consumption they are evolving into high tech enterprises, moving beyond the original business focus on the generation of electricity. Utilities are now data companies with complex information infrastructures that drive extensive use of advanced analytics to transform how utilities function and provide services.
It’s estimated that power utility data is running in the petabytes today and continues to grow daily. Organizations predict that data volumes “will be 1.5 to 2 times higher than the traditional communications industry.” Not only must utilities capture and store these overwhelming volumes of machine-generated data, but must capture data at a higher granularity, spurred by needs to drill down into systems performance and customer behaviors to understand more about current operations and future directions. Big data mining and analytics help utilities gain insights into individual customer experiences, predict peak usage and risk of outages, become more proactive for customer support, and explore new opportunities for the power industry.
Utilities have embarked on multiple endeavors to better manage and conserve electric power. Technologies include smart meters, smart building and smart power grids that work through instruments and sensors as components of frequently vast interconnected networks. Just as electric power is a valuable asset that is managed by these devices, the data and information they generate are riches that are taking these utilities – and their customers – into new worlds.
Employing smart devices and networks is making a difference for ensuring reliable electricity delivery while improving efficiencies to save energy. Smart meter sensor data keep power networks apprised of current environmental conditions to predict resource usage and potential outages. Utilities also run demand-response programs that are fed by big data analytics to further manage the power grid during peak demand, actually resulting in a lowering of power usage. Utilities are now in a continuous circuit of creating and consuming data.
Even with these technology and power grid management advances, utilities face distinct challenges. Many organizations are still trying to get their arms around what it takes to capture, store, and analyze machine-generated data that is complex, highly variable, and accumulating continuously. New processes for mining and integrating disparate datasets must be constructed, since traditional data warehouse approaches are not best-suited for handling frequently difficult datasets. New technologies must be introduced that are cost-effective, flexible, and robust for power utilities to successfully take advantage of the insights to be found in machine-generated data.
Utilities in the U.S. alone have invested millions in smart meters but are still in the fledgling state of how to capitalize on the data produced by always-on bi-directional device activity. Beyond doing a better job of operating utilities and meeting consumer demand both for reliable power supply and lower bills, like many other industries, utilities now seek to find ways to monetize smart technology data.
And like many other industries, utility companies are still learning how to work with big data analytics. Innovative technologies make it possible for utilities to explore different data modeling approaches and different kinds of questions to ask to help determine current and future trends and patterns. Just as importantly, big data analytics can help utilities figure out what doesn’t work, where negative risk may lurk, and how to work through scenarios to construct better contingency planning for internal and external circumstances.
We’re likely to see trading ecosystems for the data generated and collected by power utilities that will lead to new services and business models, similar to the transformation of the telecom industry with its big data opportunities: