Power utilities continue to generate a lot of data sources everyday. However, it has remained an open question about whether utilities will use the new data sources for significant value. There are two mechanisms to this issue; the first one is that a utility must carry out holistic data management in order to use digital data generated routinely by its sensors and systems or external sources to improve its operations and create business value. Second, the power sector must make efforts to define standards, develop applications, and share best practices for new data sources in order to speed up the time to value.
If these efforts are carried out in proper arrangement, it is a certainty to create value through a data-driven utility. To become a data-driven utility all the way through comprehensive data management practices requires a cultural shift to organizational cooperation that can change the traditional business processes. One of the characteristics of this trend is that it is irreversible once the trend is set in motion.
Today, almost every group in a utility organization should seek to optimize its work and gain competitive advantages through data and analysis on both operations and business sides. In the continually deregulated marketplace with third parties eager to serve digitally educated customers, power utilities need to take advantage of every data source that can offer more value.
Data from previously unexpected sources and in formats, speeds, scale and granularity that challenge human ability to analyze them for actionable insights are becoming available today. This is underlined by three examples of emerging data sources: Social media, unmanned aerial vehicles such as drones, and robotics. However, myriad available data sources within the organizations also confirm the effectiveness of holistic data management as the basis for the management of these new sources.
In the first place, a utility must build a strong foundation of information and communication technology (ICT) based on standards and an open architecture that integrates and ensures interoperability and backward compatibility between databases, networks, and devices. Careful documentation is necessary, as the attributes of an IED reflect different IEDs of different vendors in different ways. For example, if a preset threshold is exceeded or event-driven, data can be generated at a predetermined sampling rate.
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