When you were young, no doubt you remember hearing the tale of Rip Van Winkle, the man who fell asleep for 20 years and awoke to find, much to his dismay, the world around him was unrecognizable. The story, inspired by the author’s lament on how quickly the country was changing, could have had a happier ending for its protagonist.
If Rip had made his way to a local utility, there he would have found comfort and familiarity. In fact, some may say Rip could’ve slept for another 50-plus years and still found himself at home working in the utility field, maintaining the electric grid. Because, despite the long acknowledged and much discussed challenge of an aging workforce over the last decade, real change in utility transmission and distribution operations has been absent—at least until now.
The front lines of utilities are on the cusp of awakening from their own long slumber. The next generation is entering the utility workforce with a very different baseline. They’ve come of age in the era of mobile and wearable technology and they expect the availability of reliable data and automated processes to perform their job. The convergence of maturing, enabling technologies and the need for utilities to attract a young, talented workforce, is finally driving the momentum needed to rethink the antiquated processes and tools that have dominated the industry in favor of a new, modern approach that leverages technology to improve operational efficiency.
Asked to envision a future field worker, one could easily imagine linemen armed with tools like smart glasses, tablets and smartphones with operational visibility into the entire operational systems. One can also conceive the use of wearables like smart vests that help improve health and safety management. How about a future where drones are leveraged to more efficiently survey large areas of a solar installation to understand the impact of a storm or monitor vegetation growth? This could be a future where the data collected in the field and at the grid’s edge is used in real-time to inform remote experts. This data will enable those experts to provide planned actions to those less experienced field workers—all without ever leaving the control room.
The reality is that many of these technologies are not the future visions; they are present-day realities. Many of these digital solutions have been tested and primed to move beyond pilots and into the mainstream. However, to fully operationalize these technologies will require rethinking operations as well as work dispatch and other work activities holistically. Utilities must automate field work and improve situational awareness by not only a broader deployment of these technologies, but by employing change management processes to improve real-time connectivity and capitalize on analytics now available at the grid edge. Combined, this technology will create a foundation from which utilities can truly deliver improved efficiency as well as fast, cost-efficient responses to operational situations.
Capitalizing on these new technologies will undoubtedly require changes to foundational elements, including long established processes. One of the cornerstones to this foundation is addressing our industry’s “dirty little secret”—a.k.a data quality. Too many utilities still lack a data governance model required to provide both leaders and field workers the confidence to truly exploit these technologies and leverage analytics that would enable faster and more accurate decision making. However, defining and adopting an enterprise-wide data governance program can be daunting and sometimes in danger of being inefficient.
Instead, utilities seeking to build a solid foundation should pursue a purpose-built data governance program which requires the cleaning and governing of specific data for a specific purpose. In leveraging this type of approach, utilities must also address additional data challenges that will arise out of the explosion of technologies with built-in advanced analytics and machine learning capabilities on the grid edge. No longer will data be brought back in to the data historian to be computed, but rather the technology in the control center must be ready to accept this new data. This change requires devising a platform robust enough to process the volume of data that will be produced. Traditional backend systems were not designed for the speed and size of data processing that will now be in demand. Serializing structured messages into binary format for storage and internal platform transmission as well as data cleansing through a well-developed rules engine, can help utilities address some of these issues and ensure the data ingested is reliable.
Of equal importance to the foundation needed to operationalize these digital solutions is the utility’s GIS database. The next generation GIS database is critical not only in advancing spatial data accuracy to improve operational efficiency, but also for analytics that are needed to deploy and utilize future applications such as AMI, OMS, Distributed Generation analysis, Asset Health, and more. Accurate latitude/longitude and the ability to incorporate new data, like pictures and videos, that have supplemental and contextual meta-data, will be essential to developing new visualizations that improve situational awareness in addition to enabling faster, lower cost responses such as those related to storm outages.
There is no doubt that sensor-based technology will dominate the utility’s field capabilities in the future–it is a natural progression. Utilities are embracing sensor technology instrumented in nearly every field device installed today, so why not from the field workers as well? The ability to monitor work efficiencies for enhancing estimated time to repair is a significant benefit in work planning as well as improving customer satisfaction.
The ability to ensure that field crews’ health and safety is well maintained throughout the fieldwork process is also important. In the same manner as telemedicine, the capability for the central operations or engineering team to view what the field worker sees is also critical. It can aid in the damage assessment process, get the right material to the field faster and give engineering a real-time perspective on the work package that needs follow-up after restoration of service has occurred. This process will also provide insight to field operations supervisors on multiple-site situations, to effectively manage labor in mass outage events. With the growing availability of LTE telecommunications and utilities implementing additional high-speed grid edge communications to be utilized by the digital field worker, the possibilities of how to use this technology will only expand. Coupled with other technologies such as drones and LIDAR data, a true multi-dimensional view of field operations becomes available for all stakeholders. This new data process will lead to decreased field accidents, increased customer satisfaction, improved grid reliability and an optimized supply chain processes. Better data processing will bring a modern grid to life which will also improve recruitment of new, mobile device-savvy field workers.
While some of the technologies discussed above could be considered too far ahead of the technology curve for a utility company, it helps to realize that all of the new systems do not have to be implemented at once. Utilities should review specific use cases that are available, choosing carefully the ones that will deliver the most significant ROI for them. For example, the improvement in indices alone can make for a successful business case to utility stakeholders.
What seemed to be a very future, distant capability has now become a reality. Welcome to the 21st century, Rip.
About the author: Glen Sartain, Vice President of BRIDGE Energy Group, leads the company’s Grid Analytics Center of Excellence. He is responsible for strategy and design of analytic roadmaps for clients and the implementation of these strategies across the portfolio. Prior to joining BRIDGE, Sartain led both large and small-scale implementations of analytic solutions, as a Managing Partner of Manufacturing at Teradata where he helped build the Utilities Logical Data Model (ULDM) implemented in multiple utilities across North America. Prior to that, he served as Managing Director for CIMA Energy where he directed the building of the information management strategy including hardware, software systems and business processes, including SCADA systems.