Data Mobility Will Define the Future of Power Operations

As the power industry becomes more complex, the ability to move contextualized data will be a catalyst for more successful, efficient operations.

Power producers and distributors face a unique set of circumstances in their operations. Their product is always on, requiring constant generation and careful attention 24 hours a day, 7 days a week, around the globe to provide people with a necessary service. However, unlike most industrial operations, both the need and infrastructure for electricity are expanding incredibly rapidly. In addition, unique to the power industry, the supply chain can be disrupted instantaneously multiple times a day.

Historically, power generation, distribution, and transmission were separate, each with its own set of mostly independent processes, and a deep bench of expert operators monitoring operations from the top down. Today, however, new technology has changed the game. Solar panels, wind generation, and battery storage are putting energy onto the grid alongside traditional fossil and cogeneration plants. Conversely, use of electric vehicles, plug-in hybrids, electric heat pumps, and more are adding complexity to power delivery.

At the heart of this complexity is unpredictability. Decades ago, power operations were consistent. People used a limited number of electrical appliances in generally predictable patterns. Moreover, dispatchable generation itself was more predictable. Power generators would use individual control systems on separate assets and could operate with a top-down mentality. Operations were focused on load, with much less variability. Plants ran continuously, and experienced operators could easily make up the difference when there was variation.

Today, distributed generation has made such operations much more complex. Modern generation is not limited to power plants, but instead spread out across the entire grid, with solar panels on homes, wind farms dotting the landscape, and even generating assets on the property of industrial manufacturers. These resources can all contribute energy to the grid when they produce more than they can use. Ultimately, there are too many connected devices to have everything controlled from the top down with no automation in the middle (Figure 1).

A Shifting Workforce

So, how can power organizations manage this increasing complexity? Typically, the answer would be more people, but that solution has itself become more complicated. To operate efficiently and effectively, organizations need people who are experienced, but most of those people retired five or 10 years ago. Today, if a plant can find a new person to bring onboard, that person often has limited experience. Plants do not have the onsite staff for long apprenticeships and mentor programs, but they also cannot hand a new employee a 500-page manual and expect them to be able to run complex power operations.

The new generation of workers is used to active, intuitive learning delivered via technology. Ultimately, plants and remote operations centers are finding they need to employ technology solutions to adequately upskill the new generation, as well as digital tools to provide decision support across their employees’ tenure with the organization.

Enterprise-wide Accountability

Further complicating power operations is the fact that those operations are different at every level of the organization, especially regarding necessary reaction times. To meet today’s more complex marketplace, power organizations need visibility, communication, and collaboration from the field all the way up to enterprise business systems. Each level of that stack has different needs. At the site level, devices and assets typically provide information faster, but users also need to respond more quickly because critical changes can happen in seconds or milliseconds.

In contrast, at the top of the stack—the enterprise level—users may be responsible for thousands of miles of power infrastructure. These teams often need broader data, but the need is less immediate, as their decisions can span minutes, hours, days, or even long-scale planning across months and years. Data is at the core of decisions on every level, but the needs for that data are different for different users.

Data Mobility Is Key

Ultimately, all these challenges can be managed, but only with the free flow of contextualized data from the intelligent field, through the edge, and into the cloud. Today’s most forward-thinking power organizations are providing this data mobility by pursuing a boundless automation vision across their automation investments—leveraging seamlessly integrated systems to break down data silos.

Seamless connectivity and data mobility empower operations teams to increase productivity and operational performance with fewer resources. This type of strategy is the foundation upon which the most successful companies will build the smart grids that will dominate the future of power (Figure 2).

Better Infrastructure Means More Data

Decades ago, control system networks were proprietary, with limited capacity and constrained bandwidth limits. Over the years, however, computing and networking technology improved significantly. Similar improvement spilled over into input-output (I/O) technology controlling plants, and the result is that plants now operate using a wide variety of smart devices, all networked together for increased visibility and capability for analytics.

The change doesn’t stop there, however. With the rise of renewables has come an increased need for data. Renewable technologies have very few physical sensors. Instead, solar, battery storage, and modern wind solutions rely much more heavily on networked devices, requiring further expansion of network capabilities.

As a result, power organizations are seeing their infrastructure become even more Ethernet-based, a trend that is likely to culminate in the emergence of Ethernet Advanced Physical Layer (Ethernet-APL) as an industry standard to provide operations teams with the capability to handle more data than ever before. Unsurprisingly, forward-thinking organizations are now pursuing control technologies that are ready for Ethernet-APL.

Unshackled Data Offers More Options

Technologies like Ethernet-APL will provide power organizations with more opportunity to breakdown the silos of data that create inefficiencies in operation. Instead of data being trapped in historians at the local level due to bandwidth limitations, it will become easier for teams to move subsets of data up to enterprise-level historians. This change will also improve the value of edge devices, as these will be able to provide insight right at the asset, and to also securely move contextualized data directly into the hands of authorized users at any level of the organization (Figure 3).

Though many of the improvements that come from technologies like Ethernet-APL are still over the horizon, industry personnel are already putting the benefits of increased data mobility into action in their own organizations today, unlocking a variety of critical improvements with fit-for-purpose green energy automation software portfolios. One of those improvements is an increase in remote operations.

With more mobile data, organizations can more easily control many sites from a single location. However, data access is key. Teams are focusing on installing control solutions at the edge that are not inscrutable black boxes. Instead, they are favoring controllers that send comprehensive data back to the remote operations center, where it can be rendered on intuitive visualizations using green energy asset management software. Armed with critical data from the field, a small group of expert personnel can monitor and control a wide array of sites across a vast geographical area.

Moreover, as organizations continue to struggle to find qualified workers, while simultaneously facing more severe weather events around the globe, it has become increasingly necessary to find ways to move more control to the edge for improved grid management. With increased networking capability and improved remote monitoring functions, operators are using data in real-time to build models and machine learning applications they can use to help edge devices in remote locations make critical decisions.

Historically, remote operations required teams to wait for data to come to the grid management level, have someone evaluate it, and then send decisions back. Today, teams are operating with increased richness of data and finer granularity of samples. As a result, seamlessly integrated edge solutions can take automated actions faster and closer to the source, with grid control technologies identifying issues, making basic decisions to manage those issues, and then alerting users at the grid management level.

Data-driven AI Will Empower Operators

With so much rich data moving across every level of the power organization, artificial intelligence (AI) will begin to play a bigger role in how organizations manage their grids. This shift is already happening in other data management applications, so the potential is evident. An increase in data availability is critical to innovation, but unless teams can organize and make sense of data, it is rendered useless, or even harmful.

Remote operation is the perfect example of a situation where AI is an ideal solution. In a remote operations center with a small group of people monitoring many different sites and many generation types—wind, solar, battery, fossil, hydro, and others—it will be critical to have humans monitoring the automation for off-normal conditions. These teams will both supervise what the automation is doing, and they will interact or intervene where necessary when operations start to diverge from baselines.

However, gaining the situational awareness necessary to intervene is complex. If an operator—especially an inexperienced one—is passively monitoring automation and experiences an off-normal situation, that person will often need help. Failures can be disorienting, and in many cases, multiple simultaneous failure notices can mask the real underlying problems.

As the power and reach of AI increases, more and more teams will use it to sort through vast amounts of data to identify what is critical. Already, AI copilots are emerging within control technologies to monitor alarms and help human operators identify what needs attention, helping them make better, safer decisions when things go wrong.

Seamless Integration Is Key to Success

While data is critical to success in the power industry, it is not inherently mobile. Power organizations use a wide array of software solutions to control their operations, and if designers and engineers are not thoughtful in the way they implement those technologies, they can quickly end up with an unwieldy infrastructure that creates rather than eliminates data silos, making it hard to successfully implement the new technologies that will support the smart grids of the future.

To take full advantage of increased data mobility, thoughtful power organizations are implementing highly integrated control technologies built on a boundless automation vision. Instead of relying on control solutions from a wide array of different providers and using complex engineering to link them together, the most forward-thinking organizations are seeking out built-for-purpose software and automation solutions designed to be seamlessly integrated with each other out of the box.

Modern automation solutions providers are developing green energy portfolios built around high-quality automation platforms and deep energy industry expertise. Using these solutions, teams can standardize data in a single, scalable solution to ensure that they can move data easily, quickly, and securely to anyone who needs it, at any level of the organization.

—Rick Kephart is vice president of technology for Emerson’s power and water solutions business.