Balancing The Energy Transition, Environment, and Economics with Digital Asset Performance Management Software

The energy transition is necessary for our future. Yet energy industry leaders must balance the push to net zero with energy demands and enterprise goals today. Achieving this balance is only possible with digital technology that enables efficiency, reliability, performance, and economic viability. 

Transforming legacy industries and processes is a massive undertaking. Energy demand has never been higher. So is scrutiny of the energy and materials industry from governments, investors, and consumers.  

According to the International Energy Agency, of the $2.8 trillion estimated to be invested in energy in 2023, more than $1.7 trillion is going to clean energy, including renewable power, nuclear, grids, storage, low-emission fuels, efficiency improvements and end-use renewables and electrification. As we increase investment in generating cleaner sources of energy, existing assets and plants must be operated to be reliable, compliant, and safe. 

Software designed for accurate data analysis, predictive maintenance, actionable emissions recommendations, and a connected workforce can bring us closer to the goal of net zero faster. In a recent survey of energy and materials industry professionals conducted by Reuters Events for GE Digital, 77% of respondents said that digital transformation would be key for energy transition plans.  

Achieving ambitious sustainability goals may require capital investment, board and internal champions, workforce reallocation, and new technologies including AI/ML, predictive analytics, and advanced emissions monitoring, data analysis, and strategic implementation capabilities.  

The barriers to accelerating both the energy transition and digital transformation are significant, however, enterprises will not be able to put them off if they want to ensure business – and environmental—viability long into the future. 

Selecting and deploying the right digital solutions: Deployment and adoption remain a top concern of executives and plant-level personnel alike. Software upgrades are expensive and time-consuming, and outcomes aren’t immediate.  According to a McKinsey and Company report on digital transformation in energy, “Energy companies have failed to achieve substantial business value from digital because their approaches do not account for the unique challenges of being an energy company, which create extraordinary inertia.” The consultancy asserts that force is necessary to break this inertia – that is, making bigger and bolder digital investments rather than incremental improvements and pilot testing.

Underinvestment in software for the energy transition: In the Reuters and GE Digital research, about half of respondents believed their organizations were investing enough in digital solutions to overcome energy transition challenges. Yet only 31% of those surveyed affirmed that overall industry investment in software is sufficient to overcome energy transition challenges. This gap belies that while respondents believe they’re ahead of their transition goals, opportunity exists across the board to invest more.

New tools are needed for renewable energy: The variability of renewable energy – due to weather fluctuations and other factors – adds uncertainty and complexity to asset management, and traditional tools for unit commitment in power generation struggle to handle this unpredictability. When fossil fuel plants are used to fill the gap to meet energy demands, it’s imperative that they’re operated as efficiently as possible to reduce fuel use and emissions and maximize production to fulfill demand.

As the energy transition pushes forward, organizations with a goal of emission reduction require technology partners that are prioritizing carbon management and emissions reduction in their software development roadmap. 

Carbon Management Support: With a large number of assets running, tracking emissions might seem like an impossible task. However, with new software techniques, organizations now have the access to solutions that can: 

• Collect, reconcile and a store Scope 1, 2, and 3 emissions data, supported by AI/ML. 
• Monitor and analyze data in near real-time with the ability to leverage that data in the context of other software workloads like Asset Performance Management. 
• Report trends and generate compliance reports to enable senior business leaders to maintain emission reduction activities. 
• Strategize carbon management program adjustments and track progress against key performance indicators.  

Digital Twins: Digital twins are a key piece of the digital transformation puzzle. They create an accurate virtual replica of physical objects, assets, and systems to boost productivity, streamline operations, and increase profits. With the power of digital twins, asset-intensive organizations can increase availability and reliability, reduce risk, lower maintenance costs, and improve production as well. One great example of a real-world digital twin use case is the simulation modeling of system reliability, which can be used to identify risk mitigating action. Digital Twins can be designed and developed in collaboration with a vendor, or older digital twin blueprints can be used across hundreds of like assets to increase return and capture the full value of asset data. 

Solar Accelerators: Software developers with equipment manufacturing and hardware expertise like GE Digital are uniquely positioned to help enterprises dramatically increase time-to-value by providing pre-built configuration templates, or Accelerators. To keep up with the demand of the energy transition, we need to extend our template library to new energy sources such as solar, wind, hydro and more. By doing so, organizations can quickly extend software usage into new asset types and begin to monitor and track outputs from day one. With high growth in solar generation, energy firms need a solution specifically designed and packaged to monitor key performance indicators (KPIs), such as energy output, availability, and downtime. Making data-driven decisions to optimize performance and maximize energy production will become more pivotal as operators continue to transition to mixed fuel fleets. 

AI/ML & Predictive Analytics: The more reliable and efficient your organization operates using legacy assets, the better you can be prepared to integrate cleaner energy sources and advance toward net zero goals. Software equipped with AI/ML models to analyze asset data and provide insights, predictive analytics to optimize maintenance timing, and autonomous tuning features can help your organization manage factors like burning fossil fuel reserves, power plant heat rate, and GHG emissions.

Learn more about how energy and industrial leaders are approaching the energy transition with technology in the full Digital Energy software report, “Without software, the energy transition is going nowhere.”