Big Data & Analytics: A Widespread Phenomenon
Many industries are beginning to realize the full potential of big data and the role of analytics. The amount of data we have access to has exponentially increased and implementing analytics into the equation is key for organizations to remain ahead of competitors. Companies must jump on the bandwagon now or risk being left in the dust as competitors leverage big data to execute innovative, valuable, real-time strategies.

According to research by McKinsey & Company (McKinsey), leaders in every sector will have to address big data’s implications, since data is now a crucial part of production, labor, and capital. In 2009, almost all industries in the U.S. economy had at least 200 terabytes of stored data per company with more than 1,000 employees. By 2020, IDC predicts that the total digital universe will be 44 times bigger in 2020 than it was in 2009, totaling a staggering 35 zettabytes. Growth factors for data’s potential include volume and detail of information captured by consumers and by enterprises, multimedia content, social media and the Internet of Things.

McKinsey studied healthcare in the U.S., U.S. retail and manufacturing, Europe’s public sector, and global personal-location data. Big data provides value to each of these domains. For example, retailers can use it to increase their operating margin, the healthcare industry can create more than US$300 billion in value each year and users of services that are powered by personal-location data could rake in US$600 billion in consumer surplus.

McKinsey Global Institute (MGI) the business and economics research arm of McKinsey also identified several ways that big data can add organizational value. Big data makes information more transparent and usable. As companies are able to store increased amounts of data, performance information is more accurate and detailed, leading to better results. Forward-thinking companies use sophisticated analytics to make better management decisions, and others are using vast information for forecasting purposes. Big data also provides a more specific customer segmentation model to develop the next generation services and products (think information gathered from sensors).

Utility Industry Challenge: Overwhelming Amount of Grid Data
As big data and analytics are playing a bigger role than ever across many industries, utilities are beginning to realize the potential in the space. In developing a modern electric grid, utilities have shifted from simply adding new hardware and software applications to completely reinventing operational technology in the utility business.

Due to the availability of funding from the American Recovery and Reinvestment Act of 2009, many utilities have begun to install the necessary foundational infrastructure and communications technologies. Recent advancements in smart grid devices and applications are creating significant increases in the amount of data now available. The ability to process and make sense of the vast amount of data that is being stored and archived is the next grid modernization challenge.

Opportunity: Utilizing Untapped Operational Data and Turning it into Actionable Results
There is no doubt that the utility industry is a complex electrical, communications, IT, and human network. It takes deep domain expertise to understand these intricacies and to create value from the large amounts of data the network generates.

Big data and analytics will trump any other previously developed technology and become the foundation to optimize all current and future smart grid technology. There is a steady convergence of operation technology and information technology that is revolutionizing the way that utilities operate their networks. Transforming raw data into contextual information, analytics will create actionable knowledge and inform decision making – creating a powerful, winning, and sustainable business advantage.

Utilities are inundated with data that modern grid technologies produce. Real-time applications, smart meters, weather information, social media data, and information stemming from any of the operational components of the grid such as the outage management system (OMS), distribution management system (DMS) or supervisory control and data acquisition systems (SCADA) can yield overwhelming amounts of information. Utilities must take a deep dive into what increasing data means to their traditional operations and make the necessary strategy adjustments to improve ROI.

Solving Big Data Challenges
To help utilities effectively manage big data going forward, the marriage of data, machines and people is vital as found in the Industrial Internet (November 2012). It represents an open, global ecosystem that will allow industrial companies to move away from simply a break-fix model to a predict-and-prevent model. The open, standard protocols will enable new waves of innovation for managing, analyzing, visualizing, and controlling machines to drive intelligent collaboration.

The Industrial Internet focuses on bringing the analytical intelligence to predict and prevent problems by getting the right information to the right people at the right time. It will lead to higher levels of efficiency and productivity. For example, it has the potential to remove US$150B total in waste from major industries such as energy, healthcare, aviation, rail, oil and gas, and more. To maintain and grow the energy supply globally, US$1.9 trillion is spent every year. Just one percent savings will equal US$19B each year, which translates to US$285B over 15 years.

Industrial Internet Meets Electric Utilities
One of the first Industrial Internet products was launched in early 2013 at DistribuTECH. Grid IQ™ Insight, a new grid analytics solution, analyzes and visualizes terabytes of big data to help utilities maximize reliability and efficiency of the electrical grid.

The technology helps utilities meet their needs by managing data from the electrical grid. The platform consolidates data from a broad mix of sources, including existing grid management systems, smart meters and other intelligent grid power equipment, sensors, weather monitoring, and even unstructured social media content. It takes terabytes of data and uses advanced analytics to generate actionable information that help to predict and proactively resolve issues that impact the performance of today’s power grid. Data helps to drive better behaviors and patterns, which allows utilities to improve the ability to meet the expectations of its consumers.

The concept for this solution began more than two years ago, and is an example of integrating energy hardware and software tools to enhance visibility and control to the grid. The knowledge gained through tools like this combined with deep domain expertise of how all of the systems work together leads to powerful utility innovation. Many industrial companies like GE recognize big data analytics as a crucial next step for utilities to maximize the value of their data and systems.

Industrial Internet platforms offer numerous benefits to utility customers, including:

• Helping utilities to quickly identify and solve some of their most pressing data challenges, with data analytics and domain expertise
• Providing real-time information in a closed loop system to help utility companies better visualize, analyze and optimize data on the grid
• Innovation through an iterative rapid prototype process that has minimal disruption to utility resources
• Hosting a developing commercial library of analytic applications that spans across the grid from the time electrons leave the power station to when they are consumed by the end user

Solar energy installations have increased 116 percent year-to-year, but most utilities cannot track distributed energy day-to-day. This solution can combine solar interconnection, weather, and meter data to model distributed energy’s effects on network reliability. It also tells customers how much money can be saved on a daily basis by utilizing solar power.

A utility’s smart meter platform transmits massive amounts of energy consumption data – think hundreds of millions of readings and many gigabytes of data. Utilities face the challenge of not only collecting the data, but managing and storing it as well. The technology analyzes smart meter, customer, and network data to help utilities and consumers improve their energy efficiency, reduce revenue loss and better understand energy consumption trends.

According to Electric Power Research Institute (EPRI), power outages and power quality disturbances greatly affect the U.S. economy, costing utilities and consumers more than US$150 billion annually. The grid analytics solution enables utilities to identify system outages quickly via improved visualization and analysis of their systems, minimizing outage times and greatly reducing costs associated with extended system outages.

Approximately 500 million registered Twitter users generate over 340 million tweets daily. That’s about 320 thousand daily tweets from a typical utility’s customer base. The social media analysis component can identify trouble spots on Twitter – and therefore outage locations – before customers call in. This enables the energy provider to respond more quickly to outages thereby minimizing customer disruption.

Putting the Platform to Use
One customer chose the combination of GE’s outage management system (OMS), distribution management system (DMS) and grid analytics solutions. The offering is designed to capture reliability data during restoration processes and to provide the resulting operational data that reflects the performance of the utility during specific time periods, weather events or for an entire year. The system is able to:

• combine and analyze frequency and duration of every single outage
• voltage levels across the grid
• compensation currently and compared to other time periods
• weather histograms including rainfall, wind data, and temperature data all in real-time on one computer monitor.

When it comes time to report to regulators, the information can be constructed in a way that aligns with the regulatory standards, such as in different geographic views. All indicators can be calculated per electrical set, city, circuit, and installation. Additionally, the platform helps the utility improve prioritization of outages based on the number of consumers, and view critical customers or the size of the customers affected in one system.

A Natural Fit for Geospatial Needs
As utilities become more aware of the power of Geographic Information Systems (GIS) data, they are asking how they can extend the reach of their own GIS data and gain higher return on investment. With strong engineering capabilities within their companies, utilities are keen to increase productivity based on their ability to access, visualize, and analyze their grid data.

For this reason, Google recently integrated Google Maps data into GE’s Smallworld™ electrical, telecommunications, and gas applications. The geospatial product suite helps industries design and model complex network infrastructures while supporting asset management lifecycle processes. The platform will help utilities increase productivity based on the ability to visualize and analyze data. The partnership will also enhance the existing network visualization capabilities and will allow utility customers to receive incremental efficiency and productivity of operations in the field. Utility users are able to view a familiar, simple, and intuitive user interface overlaid on their geospatial applications. By enhancing the ability to visualize data on a map, utility customers will be able to quickly provide their end-use customers with important information such as outage restoration times and will help to more efficiently manage their network assets. The agreement will also deliver solutions for applications such as business intelligence, engineering, web clients, schematics, corridor management, and enterprise gateway.

Google’s mapping content will form an integral part of a developed set of focused applications for the web, mobile devices, and desktops and will strengthen existing geospatial capabilities of Smallworld products. The DMS and OMS also will utilize Google’s mapping content in the context of operational control of electricity networks. For field operators Google’s Android platform will be utilized to augment the existing portfolio of mobile products.

Next Steps for the Industry
With the utility industry becoming more complex and evolving in such a significant way, utilities must adapt to a more proactive approach in managing increasing power demand. They must shift to real-time and predictive analytics, moving away from the traditional reactive ‘as needed’ model.

Utilities can do this through taking additional risk, investing in cutting-edge technologies and partnering with advanced technology teams in R&D efforts. A modernized grid is essentially an ‘energy Internet,’ delivering real-time information and knowledge – providing the visibility and control to empower smarter energy choices and deliver unprecedented new benefits. By connecting minds and machines, we can push the boundaries of physical and material sciences to make the electric grid more efficient and reliable.

About the Author

Brian Bradford is Director of Product Marketing for Software Solutions under GE Energy Management’s Digital Energy business. He is responsible for the strategy, commercialization and positioning of all DE’s grid modernization software businesses which are targeted at providing visibility, control, and analytics of electricity throughout the grid.

Brian began his career in energy in the mid-nineties and proceeded with a seven year career at Enron Corporation where he focused on business development and strategy in the finance, international, and broadband divisions. After Enron, he was a new business development consultant for Mirant Corp and the Jamaica Public Service Company. In 2005 he became Director of Strategy and New Business Development at NSTAR Corporation (now Northeast Utilities) and served as President of telecommunications subsidiary, NSTAR Communications Inc. Post NSTAR, he was Director of Strategy Consulting at clean technology start up GridPoint Inc. Brian joined the GE team in 2011. He has an MBA from Harvard Business School and an undergraduate degree in Finance from the Wharton School of the University of Pennsylvania.