The digital power plant of the future

The power industry must overcome significant challenges in its journey to digitize, but successful transformations could result in the next S-curve of performance.

Like many other industries, power generation is becoming increasingly digitized. Yet many players are only now taking steps to create value from tech-enabled initiatives and establish new ways of working. In fact, there are no global end-to-end cases of digitization in power generation; even the most technologically advanced players have implemented only a small number of isolated digitization use cases, which are often not directly tied to business value.

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Simply put, power companies are not nearly as advanced as they could be, so operations and maintenance costs are higher than they could be. Further complicating matters, cost pressure for thermal assets—namely, coal and gas—continues to rise because of ongoing power-market liberalization and large-scale deployment of various renewable energy sources, such as solar and wind in Europe and the United States. Similar developments are expected in Asian markets, such as in Japan. These conditions have led to consistent, major pitfalls across markets.

Tech-enabled transformation combines new technologies with traditional improvement and can provide large value across four key areas: operations; maintenance; energy efficiency; and health, safety, security, and environment (HSSE). In this article, we explain what a successful digital transformation across the four areas looks like as well as the most important themes to create value.

Power-plant digital transformations face common pitfalls

Thermal generation still dominates the global fuel mix, with coal and gas making up 62 percent and representing 16 petawatt-hours (PWh) today. Our research shows coal and gas contribution to the fuel mix will stay constant until 2030, after which it will decrease toward 2050 (Exhibit 1).

Coal and gas still dominate power generation—and will likely continue to do so through 2030.
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Because of cost pressure from the recent shift to renewable energy sources, some utilities have completed several rounds of lean transformation programs to increase the competitiveness of their assets. While these “traditional” programs were successful in the short term, our research shows that end-to-end digitization can realize additional average earnings before interest, taxes, depreciation, and amortization (EBITDA) potential of 20 to 30 percent.

However, those setting off on their transformation journeys face five common pitfalls.

Lack of defined vision and new roles

Many companies across industries fail to articulate a clear vision for their digital transformations. As a result, workers are often left guessing how digital and analytics can improve their day-to-day tasks; some might even perceive the transformation as a threat rather than an opportunity (for example, they may believe automation will make their jobs redundant). When it comes to power-plant transformations, many companies make the same mistake.

Explaining how different roles within a power plant are affected shows workers that successful digital transformations make smart use of data and efficient ways of working to focus on performance improvement. This means that digitization will lead to updated roles, rather than reduced headcount. Some of these updated roles include the following:

  • Control-room operator. Digital technologies can reduce paperwork for documentation and reporting—as well as the number of rounds to inspect equipment, observe performance, or detect technical problems.
  • Outage and maintenance planner. Analytics can support the prioritization and sequencing of maintenance work.
  • Power-plant manager. Digital and analytics can offer real-time views of asset status, including the financial impact of reduced performance.

Use-case selection and prioritization not based on value

For power plants, an end-to-end digital transformation consists of use cases that are designed, built, piloted, and rolled out. Yet many companies prioritize use cases based solely on individual interest instead of business value. For example, one European utility prioritized a tool to support the operators on their shift inspection round. While this tool standardizes the inspection process of the operator rounds, it does not create high business value due to its narrow applicability. At the same time, large opportunities in the maintenance strategy and its execution are often untapped after being initially overlooked and deprioritized.

Focus on solutions instead of ways of working

Many power companies focus on implementing new tools—but neglect new ways of working. Tools are sometimes not adopted and eventually fall by the wayside. However, by integrating new ways of working, processes and standards are not only adopted but also become standard procedure. As an example, an advanced heat-rate optimization model helps to increase plant performance by providing operators with real-time recommendations on how to calibrate the most crucial parameters. In addition to building the advanced-analytics model, operating procedures must be adapted to enable operators to follow the tool’s suggestions. Even more importantly, the model configuration needs to be cocreated with the operators to build the credibility of the tool from the beginning, which can help ensure that the recommendations are used in day-to-day operations.

Data availability and structure

For many use cases the availability of consistent data is crucial. Depending on the situation, various shortcomings are observed: 1) data quality is not sufficient, including the frequency and detail of collected data, 2) data are not standardized across assets within one company, and 3) data are not accessible outside the plant perimeters.

All these factors complicate the fast design and deployment of advanced-analytics use cases. To overcome these challenges, a two-speed data and IT architecture is often implemented that satisfies the specific needs of prioritized use cases. Thus, the business value can be proven and captured and the more time-consuming migration to a new comprehensive data and IT system can be postponed without interfering with the progress of the use-case implementation.

Reliance on small siloed IT teams

The lack of digital talent is among the biggest hurdles in digital transformations, regardless of industry. For power companies, transformations are often helmed by small IT teams and exclude engineers from operations and maintenance. Our research shows that successful power-plant transformations emphasize digital capability building across the organization early on in the process of reskilling or upskilling internal resources. Doing so serves as both motivation and confidence booster for the organization and can lead to sustainable change.

Lack of focus to build a model power plant early

Companies that neglect to model the transformation may implement digital solutions across a number of different assets, subsequently limiting each asset’s role in the transformation. That strategy may have its advantages in other industries, but power-plant transformations require a more comprehensive and selective approach early: one or two power plants should be picked as “lighthouse” stations for the transformation. The selections of these model stations should be taken using critical factors, such as use-case value and buy-in from plant leadership. The value-creation potential should be significant enough to influence the plant portfolio, and plant management should be motivated to drive the implementation.

The power plant of the future: What a successful digital transformation looks like

Equipped with outlines of the common pitfalls, power companies and plant operators can focus on shifting from a traditional power plant to a digital power plant. This transformation must occur across four key areas: operations, maintenance, energy efficiency, and HSSE (Exhibit 2).

To achieve these ambitions, companies must transition operations and maintenance from traditional to digitally enabled.
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A fully digitized power plant will focus on optimizing performance in real time and operating in a safe and stable manner—supported by automated reporting, guided issue resolution, and digitized controls walks.

Process efficiency. Mobile devices can help standardize operator rounds and automate documentation. In addition, inspection times can be reduced with radio-frequency identification (RFID), which can send automated push notifications about equipment performance and repair history. Processes can also be supported by IT with real-time monitoring of key performance indicators as well as the tracking of improvement measures and IT-supported operator shift planning.

Flexibility. Analysis and optimization of plant-efficiency parameters should be based on readily available data during start-up and the time it takes to ramp up. This can be supported by standardized procedures with real-time recommendations for operators. Finally, individual start-up performances can be tracked by shift to identify and promote best practices.

A fully digitized power plant will focus on optimizing performance in real time and operating in a safe and stable manner—supported by automated reporting, guided issue resolution, and digitized controls walks.


World-class reliability should be maintained while reducing planned outage time and maintenance costs. Data analytics and digital-process support are key.

Maintenance strategy. Equipment can be monitored with real-time, advanced analytics to reduce time-based maintenance and increase predictive maintenance. In addition, smart sensors that directly feed into a digital twin can provide improved insights on plant condition, spare-part management can be integrated based on work orders and equipment condition, and outage cycles can be planned according to international best practices.

Outage and project execution. Digital control towers can monitor planned and unplanned outages to track progress in real time and automate the calculation of potential delays. Control-tower meetings based on key performance indicators can further identify potential delays and determine the most-effective countermeasures to avoid further disruption. Drones can carry out inspections during outages, consequently reducing the need for scaffolding around hard-to-reach places, such as boiler walls or cooling towers.

Reliability. Bad-actor programs, which identify gaps in reliability strategies, can collect data from the distributed control system, digital twins, or other sources and quickly calculate any impact on plant performance. Root-cause assessments using advanced analytics, trend analysis, and anomaly detection can help identify the best solution.

Energy efficiency

Heat-rate losses and other measures of efficiency should be not only regularly analyzed and based on performance reports but also visualized in real time. As a result, certain immediate actions can be triggered to resolve issues as quickly as possible.

Heat-rate losses and other measures of efficiency should be not only regularly analyzed and based on performance reports but also visualized in real time.

Fuel efficiency. Digital twins of plants can be constructed based on comprehensive thermodynamic models of all units. Doing so can enable automatic real-time analysis of plant parameters and comparison with optimal conditions to generate recommendations for plant operators. A digital dashboard in the control room can provide full transparency on improvement levers and financial impact, and a virtual bunker can allow for optimal fuel mixing based on real-time plant conditions and market prices.

Chemical-consumption reduction. The recommended levels of chemical use can be automated based on a digital model of the plant’s water cycle and properties. Water-parameter trend forecasts can also be made to automate chemical probing, dosing, and analysis, helping to avoid peaks in emissions.

Auxiliary power efficiency. Recommendations on the optimal operating points of equipment can be automated according to plant-operating points. Dashboards can provide data on auxiliary power consumptions and automated, analytics-based assessment of usage patterns. And auxiliary equipment instructions can be standardized and followed by all operators.

Health, safety, security, and environment

The end-to-end digitization of HSSE processes can be accomplished with automated monitoring and documentation to aid both root-cause analysis and the creation of preventative measures.

Digital technologies can provide a real-time dashboard on plant emissions and limits as well as support automated monitoring of incidents, documentation, and root-cause-analysis and prevention measures.

Even though many utilities have improved power plant performance in recent years to cope with the new market environment and the competition, we see that an end-to-end digital transformation of power plants could still generate a large bottom-line value to utilities. Executives will need to achieve a triple transformation in the near future to succeed.

This approach requires executives to place equal emphasis on transforming business, technology, and the organization. Doing so ensures that use cases are not only developed and implemented but also tied to value. Two-speed IT and data architecture can provide the backbone for rapid deployment. And updated governance, roles, and skills will inform the new ways of working, helping to establish the transition plan in line with the business road map.

Recent technological advances have made power-plant digitization possible and market pressures have made it urgent. Those that make the right moves can create value in the short term and lasting change in the long term, both of which will help master the next S-curve of asset performance—a necessity in an increasingly challenging market environment for coal and gas power plants.

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