A Holistic Data Analytics Strategy is Critical for Smart Grid Projects

By Robert Sherick, Southern California Edison, and Steve Ehrlich, Space-Time Insight

Smart grids will figure prominently in the power landscape of the future. In cities, states and countries the world over, the foundation is being laid for infrastructure, products and services that incorporate greener power sources and innovative technologies that maximize efficiency.

Holistic Data Analytics Strategy

This is a vital evolution, but one that’s still in its early stages. Fully modernized smart grids will take time and some trial and error to get right, which is why efforts to test, validate and measure the success of approaches are imperative.

A smart approach to smart grid development is especially important in California.

The state’s goal is to have 33 percent of its power mix come from renewable sources by 2020.

Utilities, power generators, grid operators, the public utilities commission and other industry players all have a stake in identifying technologies that support this objective.

Holistic Data Analytics Strategy

Case in point: as one of California’s (and the nation’s) largest electric utilities, Southern California Edison (SCE) is focused on finding ways to deliver power to consumers safely, reliably, sustainably and cost-effectively.

This is the impetus behind the Irvine Smart Grid Demonstration (ISGD) project, which is managed and led by SCE and funded through the American Recovery and Reinvestment Act of 2009.

The project is designed to demonstrate the interoperability and efficacy of smart grid technologies within a controlled environment. ISGD will be deployed at the University of California, Irvine (UCI) and SCE’s MacArthur Substation in Newport Beach. The location sites are typical of heavily populated areas of Southern California in climate, topography, environmental concerns and other public policy issues.

Data analysis is a central part of the ISGD. SCE needs to keep close tabs on what’s working and what’s not so it can suggest improvements to the design and performance of the smart grid technologies that are part of the demonstration project.

But this task can get challenging as more streams of information are generated by sensors, devices, equipment and systems throughout the grid.

big data

The following are some key considerations organizations need to consider as they launch smart grid projects that require in-depth awareness of an array of moving parts:

1 Volume. Massive data volumes otherwise known as big data challenge many organizations, and this trend is particularly acute in the power industry. Newer technologies such as synchrophasors, advanced distribution equipment, smart meters and smart appliances, in addition to traditional operational systems and devices, are producing an avalanche of real-time information. Managed wisely, this data is a valuable asset that helps stakeholders efficiently orchestrate grid operations, stay on top of potential issues and predict requirements. Managed poorly, it can become an overwhelming burden that’s problematic to store and maintain. An ability to process and interpret large quantities of data quickly is key.

2 Complexity. Volume, however, is only one part of the equation. In smart grid environments, the diversity of data sources and the pace at which information is generated add complexity to information analysis that is unprecedented.

For example, data may be generated in real time by thousands of devices and source systems from smart meters and in-home thermostats to sensors on solar panels, transformers, circuits and other infrastructure.

When multiple sources and formats of data are in play, switching between application screens, comparing numbers from piles of spreadsheets or weeding through static text documents to find and analyze critical information is neither effective nor efficient.

These manual, ad-hoc approaches to data management are too slow, cumbersome and prone to error. Meanwhile, customizing point-to-point digital integration between devices and systems is cost-prohibitive.

Organizations need a way to cost-effectively correlate, analyze and present information as a cohesive whole so decision-makers can understand the big picture.

3 Governance. Just as smart grid assets and devices are widely distributed, so is the responsibility for managing all of the data components involved.

Multiple stakeholders might need to take part in smart grid decision-making, from operators and technology providers to back and front office utility company staff, policymakers and even consumers.

These multiple stakeholders have traditional uses for “their” data.

Understanding the usefulness this data provides to others will take time and might lead to new processes within an organization.

Data analysis solutions therefore must consider the needs of diverse information consumers and varying levels of access.

4 Security. Finally, data security and privacy issues require careful consideration.

Smart grid data contains more detailed data on customer energy usage and electric system operations.

Customer confidentiality and privacy must be protected.

As the data collected about consumer behavior becomes more granular, protecting this information is essential.

Equally important is maintaining a secure, reliable electrical system. The increased points of entry to a smart grid must be secured and managed to maintain overall system reliability of the transmission and distribution systems.

A robust cybersecurity system is critical to the success of the smart grid, and monitoring this cybersecurity landscape will require analyzing security data through improved visualization tools.

Bringing it All Together With Situational Intelligence

Because a smart grid project encompasses multiple technology assets, big data sources and stakeholders, a secure, situationally aware approach to information analysis is critical. Decision-makers must be able to digest and analyze large volumes of real-time information holistically instead of in a piecemeal fashion where important connections might be missed.

Bringing it All Together

In the case of the ISGD project, SCE selected a situational intelligence software solution from Space-Time Insight that combines multidimensional spatial maps with sophisticated analytics to build visualizations of structured and unstructured data from different underlying domains.

This solution serves as the eyes of the ISGD, enabling project participants to quickly see, understand and assess the performance of the many diverse technologies deployed within the demonstration. For example, SCE can use the situational intelligence software to do things such as: analyze the costs and benefits of circuit voltage optimization; understand the impact of electric vehicle charging on off-peak energy consumption; and keep tabs on on-site solar generation and energy storage systems and overall grid reliability. Key to making this work is the software’s ability to correlate and analyze real-time and historical data from diverse sources seamlessly so decision-makers get an accurate, complete view of what’s happening throughout the smart grid at a glance. Also important are innovative visualization techniques such as color-coding, 3-D representations and animation, which help information consumers intuitively make sense of complex data.

Looking beyond the ISGD project, SCE anticipates the technology deployed in ISGD will be adopted increasingly throughout the SCE service area. Interconnected devices and information—programmable thermostats, electric vehicles, storage devices and distributed generation—will require improved monitoring and control systems. The optimization of the interaction of these devices within the distribution grid will be a large component of a smarter grid. This device integration and the associated data analysis will be the next challenge for utilities. The increasing volume and complexity of data from these devices also will require a renewed data governance model and a highly secure cybersystem to ensure data is collected, processed and visualized to enable smart, secure decision-making.

As smart grid projects gain momentum, power industry stakeholders must be able to closely track the cost, benefits and impacts of new technologies and understand how all elements of the grid are coming together in real time to bring greener power to consumers.

With so much data streaming in from so many sources, a holistic, situational approach to information analysis will help organizations transform mountains of smart grid data into valuable insight that helps them forge a safe, sustainable and successful path.

Robert Sherick is principal manager for grid advancement and power systems technologies for Southern California Edison, one of the largest U.S. electric utilities. SCE delivers power to more than 14 million people in central, coastal and Southern California.

Steve Ehrlich is senior vice president of marketing and product development for Space-Time Insight, a provider of next-generation situational intelligence solutions.

Go to http://pgi.hotims.com for more information.

Utilities need to consider four things as they launch smart grid projects: volume, complexity, governance and security.

As smart grid projects gain momentum, stakeholders must closely track the cost, benefits and impacts of new technologies.

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