Achieve business outcomes that matter
Measure, manage, and operationalize your sustainability goals – including decarbonization, energy resources management, and reduced WAGES.
Achieve operations visibility and AI-based optimization, linking plant-floor actions to your enterprise sustainability initiatives.
A system of record to automate accurate GHG data collection, provide valuable insights, and identify ways to reduce carbon emissions
One modular solution to connect, see, control, and optimize DERs from a technical and an economic standpoint
Reduced operational costs and risks using Digital Twins, machine learning and predictive models
Increased network reliability
Advanced analytics to predict future asset and process performance for reduced variability and improved operations
Optimized asset performance to reduce risk and improve safety, reliability, compliance, and efficiency
Optimize assets and processes – from plant-level operations to the enterprise – with self-service process analytics software.
Minimized potential impact of anomalies
Comprehensive visibility of asset health for rapid situational adjustments with quality information
Streamlined mechanical integrity solution to reduce risk, maintain compliance and optimize resources
Develop, implement, maintain, and optimize asset strategies to effectively balance cost and risk
Operational visibility and analysis to reduce asset failures, control costs and increase availability
Performance Intelligence with APM Reliability is your partner in meeting your plant and fleet performance goals.
Predictive analytics software, helps prevent equipment downtime by detecting, diagnosing, forecasting & preventing emerging failures.
The AI-powered product automatically explores the space of operation of gas turbines, builds a machine learning model, and continuously finds the optimal flame temperatures and fuel splits to minimize emissions
BoilerOpt works within existing plant technology to improve boiler productivity and air-fuel ratios in a closed-loop system
Pre-built templates for equipment health monitoring, asset strategies, and process workflows
Operator rounds efficiency and operational impact
Secure and scalable data connectivity, analytics, and application services
Services and solutions to reduce vulnerability and identify, detect, prevent and protect
Turnkey solutions to reduce vulnerability and identify, detect, prevent and protect assets and systems
A globally recognized benchmark for procurement of OT secure products.
Strengthened device security across the development lifecycle
Informed decision making with data and insights from across the enterprise
Native cloud service for a data historian.
Safe and secure management and orchestration of the distribution grid
Network-level optimization with high-performing distribution power applications
Overcome foreseeable load variations
Minimized disruption of service even in extreme weather conditions
Effective management and orchestration to unlock the power of renewables and DERs
Increased output and energy production at times of highest demand
A common network view to ensure electrical integrity, network validity and infrastructure management
Accurately model your asset network, support traceability, help assure data completeness, & support integrity management
End-to-end network connectivity modeling and data workflow management
Software designed to help grid operators orchestrate the grid
Increased efficiency and reduced costs
Secure-by-design connectivity and certification management, and faster operator response
Faster operator response and increased efficiency
Centralized visualization and configuration, digitized processes and intelligence
Full visualization and control seamlessly across devices, including phones, tablets and desktops
Best practices and proven deployment learnings
In-depth understanding of how GE Digital software can help your operations
Holistic performance management for today’s connected enterprise
Management of fast-moving processes as well as slower moving, labor-intensive jobs
Cost savings with improved manufacturing overall equipment effectiveness
Batch automation, regardless of the underlying equipment
Data analysis for quick identification of defects and better optimization of processes
Unified manufacturing data from disparate systems to better meet changing consumer demands
Procedures managed in an electronic format for consistency and predictability
Optimized production with better planning
Improved throughput with greater efficiency and lower costs
Materials to help you better understand GE Digital software and its robust functionality
Integrated solutions for improved efficiency and sustainability while supporting business growth
Energy management for the zero carbon grid
Reliable mobilization of network assets to ensure maximum transmission of energy from multiple sources
Integrated solutions suite for energy market management
Decentralized data collection, data volume handling, and remote management
Getting the most benefit out of digitization and industrial IoT
Services that deliver best-in-class results
Rapid digital transformation wins based on industry-proven value cases and ROI
Best practices for your industrial processes to help build and maintain operational resilience
GE Digital’s expert service and support teams create value and deliver on business objectives
Expert service and support teams to maximize the benefits from your IIoT software
Improved efficiencies, optimized production and quality and reduced unplanned downtime
Increased reliability and availability, minimized costs, and reduced operational risks
Increased value from your equipment, process data, and business models
The cornerstone of your journey to operational excellence
Operational excellence including improved reliability, reduced costs and managed risk
GridOS, the first grid software portfolio designed for grid orchestration
Reduced operational costs and risks using predictive models
Enhanced overall situational awareness
Field-connected operations and management
One modular solution that enables grid operators to connect, see, control, and optimize DERs from a technical and an economic standpoint
Operational efficiency and reduction in build costs while meeting regulatory regulations
Reduced operational and new build costs and improved field inspection productivity
A holistic picture of the grid, reducing cost and complexity from traditional inspection approaches
Optimized operations to best meet changing consumer needs
Reduced variability and improved operations.
In-depth understanding of our software and its functionality
A clear a path to operational transformation
Maintain consistent quality and reduce cost per ton
Optimized costs and improved reliability while reducing risk to keep your teams and communities safe
Streamlined end-to-end operations driving high-volume, high-quality production
GE Digital software is the backbone of modern plant operations
Improved reliability, increased availability, and reduced O&M costs
AI/ML to make your gas turbine's fuel and air controls smarter
Increase energy production at times of highest demand without costly maintenance adders or adversely impacting the maintenance interval
Inclusive outsourcing services that deliver best-in-class results
Achieve digital transformation
Expert service teams to maximize the benefits from your IIoT software
Reduced costs, lower risk, and faster response times
Analytics to predict future asset and process performance for reduced variability & improved operations
A common network view to ensure integrity, network validity and infrastructure management
Mission critical software to better operate, optimize and analyze your work to deliver results
Locate the best partners to meet your needs
Digital transformation acceleration
Technical and domain expertise that complements GE Digital’s industry leading applications
Assistance to accelerate your digital transformation and put your industrial data to work
Deep domain knowledge and technical expertise
Product training, industry education, and rigorous certification programs
More efficient and secure electric grid, greater sustainability and waste reduction
Solutions for today, scale for tomorrow
Increased reliability and reduced reactive maintenance leading to higher efficiency and reduced costs
Using Digital Twin blueprints, GE's Industrial Managed Services team monitors 7,000+ global assets
Understanding of the latest thought leadership that can be applied to your operations
Understand how our software and services help our customers solve today's toughest challenges
Experienced team dedicated to customer success
Success stories and product updates from the world of Electrification Software
Analyst and third-party expert opinions of Electrification Software and our software and services
White papers, product overviews, and other content to help you put your industrial data to work
Experience in leading edge software development and business working with best-in-class leaders
Understand how Electrification software and services helps our customers solve today's toughest challenges
Blog
Nations across the globe and the energy and industrial sectors are experiencing the impact of the energy transition, as governments and corporations progress toward reaching a low-carbon footprint. The impact varies depending on net zero goals, investment, infrastructure, and workforce readiness.
But more than reaching net zero goals, the real end game is to achieve carbon negative, when you remove more carbon dioxide and carbon dioxide equivalent (CO2e) greenhouse gasses than you emit. It will happen in phases, and some countries and industries will reach goals faster, but one point is unanimous among industry experts: without Artificial intelligence (AI) there is no energy transition and no carbon reduction.
According to a BloombergNEF (BNEF) report published by the World Economic Forum, AI has the potential to create substantial value for the global energy transition. Based on BNEF’s net zero scenario modelling, every 1% of additional efficiency in demand creates $1.3 trillion in value between 2020 and 2050 due to reduced investment needs. Using AI in the energy sector could achieve this by enabling greater energy efficiency and flexing demand.
So it’s no surprise the Global Artificial Intelligence Industry Forecast indicates that the global AI market was valued at around $62.35 billion in 2020, and it is expected to grow at a compound annual growth rate (CAGR) of nearly 40% during the forecast period from 2021 to 2026.
At GE Vernova, the definition of Artificial Intelligence represents the ability to 1) Sense, 2) Reason, 3) Learn, and 4) React with human-like levels of intelligence. Machine learning is a subset of AI involving the use of algorithms to learn from data and improve performance on a specific task without being explicitly programmed.
After decades of collecting information, companies in the energy industry, such as power generation, oil and gas, chemicals, metal and mining, are often data rich but insights poor, making it almost impossible to navigate the millions of records of structured and unstructured data to find relevant information. This challenge is particularly important when engineers are troubleshooting new issues on highly complex systems to find the most relevant procedures, machine performance data, history of operations, and instances of relevant issues on similar subsystems. Engineers are often left relying on their previous experience, talking to other experts, and searching through piles of data to find relevant information. For critical issues, this high-stakes scavenger hunt is stressful at best and often leads to suboptimal outcomes, said McKinsey & Company in its report on the promise of AI in industrials.
In a recent study conducted by Verdantix on industrial AI analytics, researchers noted that the early days of advanced AI analytics saw improvements in training techniques, the proliferation of inexpensive data acquisition, cloud-scale big data acceleration and the arrival of purpose-built computer hardware to speed up development. Building on these established workflows, industrial firms are investing in and seeing success with several core AI technologies including the following:
In this same study, Verdantix compared GE Vernova with several other vendors showing which vendors have maximized the use of AI in seven use cases to help organizations to accelerate through the energy transition. GE Vernova was one of three vendors to offer software in each category:
Asset-intensive industries need to maintain critical assets and equipment free of failures and unplanned maintenance, otherwise it can negatively impact operations and quickly bring millions of dollars of cost.
By using predictive analytics enabled by digital twin blueprints, Asset Performance Management (APM) software provides early detection of pending issues, diagnostic analytics and indicates probable cause, suggesting maintenance alternatives. Deploying APM for customers, GE Industrial Managed Services has demonstrated $1.6B in Operations & Maintenance (O&M) savings.
Let’s break down the AI embedded in APM. Digital Twins are build based on OEM expertise and then trained to be more accurate and high performing with AI/ML. AI for Digital Twins allows for cloud customers to get time to action projections that support the predictive element of the use case. AI/ML then takes the data from catches and uses them in future decisions—which is the intelligence piece of the software. More data = more accurate projections.
Energy market data is more diverse and decentralized than ever, especially now with the addition of renewable energy into the mix. An overwhelming amount of information bombards energy traders daily in today’s market, with the sheer volume and complexity making uniting and analyzing the information quickly enough to anticipate market movements in time to capture value challenging.
GE Vernova has created a unique solution that leverages advanced AI to produce generation and price predictions, then combines them with a risk management approach matched to the customer’s risk profile.
For deregulated market stakeholders, especially those with renewable assets, GE leverages AI/ML-powered energy market insights to provide day ahead recommendations to improve portfolio for wholesale market participation.
For regulated markets, GE Digital’s Fleet Orchestration empowers utilities to seamlessly move from day-ahead planning to real-time operation. To aid in the energy transition, models using AI and machine learning result in greater accuracy in predictions and improve productivity across the workflow. Fleet Orchestration uses intelligence, analytics, and seamless communication to provide real-time visibility to generation and capacity predictions and unit commitment optimization.
Leading Italian digital energy company Sorgenia uses GE Vernova’s APM Reliability software deployed in the cloud to maximize the reliability and efficiency of its state-of-the-art, combined-cycle gas turbine power plants. According to the company, the software has given them insights to better plan maintenance around annual outages, specifically at their Termoli and Modugno plants. Doing so allows them to avoid unnecessary downtime on critical assets, such as heat recover steam generators or condensers, which in turn allows them to operate at higher efficiency and satisfy their more than 450,000 customers’ need for electricity. Read more in the 2022 GE Sustainability Report.
Manual tuning of gas turbines traditionally occurs twice a year during seasonal transitions. However, weather is unpredictable, and fuel is a major expense for thermal generators. With the integration of AI/ML, GE Vernova’s Autonomous Tuning enables power generators worldwide in achieving automated gas turbine tuning to optimize for all current conditions and transitional modes. The gas turbine performance software solution allows for finding and maintaining the turbines optimal operating conditions, referred to as the ‘best zone’ or ‘sweet spot’. The AI/ML algorithms continuously analyze real-time data to adopt and optimize to variable changes, such as shifts in environmental conditions, variations in fuel properties, and physical degradation.
As a result, power generation plants have achieved impressive environmental and efficiency improvements, including 14% reduction in carbon monoxide emissions, 10% to 14% decrease in nitrous oxide emissions, and noteworthy reductions in fuel consumptions and CO2 emissions, ranging between .5-1%.
“With Autonomous Tuning, GE Digital has introduced a practical industrial example of the use of machine learning in closed loop supervisory control, and all running at the Edge,” according to Joe Perino, Principal Analyst at LNS Research. “This is a real-world application of AI for decarbonization with tangible reductions in emissions and fuel for gas turbine operators.
GE Vernova is collaborating with large power generation organizations by providing a cloud-based image analytics application that automates the manual data collection to insight generation process. It enables seamless collection and transfer of image data to cloud which is then processed by AI-enabled algorithms to generate valuable insights and triggers actionable alerts. Thus, it empowers customers to make informed decisions fast and take proactive measures to optimize their asset and operational performance. Autonomous imaged-based inspections can save a significant amount of cost. Research shows approximately 20% cost savings on labor and asset maintenance.
Effective emissions management must begin with accurate measurement of Greenhouse Gas Emissions (GHG). Not only to align with stricter emissions reporting mandates, but to enable progress on carbon negative goals. Data must be combined with analysis of what methods would be effective to reduce emissions and what the impact would be on the organization.
GE Vernova’s recently launched CERius™ Emissions Management Software automates more accurate GHG data collection and reporting, performs predictive analysis including what-if scenarios, and recommends actions to reduce them. The software eliminates manual data collection and siloes between sites and departments and effectively ties emissions data to decarbonization strategy.
In summary, AI can be a powerful tool in the fight against climate change and in achieving carbon negativity. By applying energy transition technologies built with AI/ML strategically in various sectors, we can reduce carbon emissions and increase the capacity to remove carbon from the atmosphere, ultimately helping to address the global climate crisis.
Global Marketing Director, Power Generation and Oil & Gas
Francis brings 20 years of experience in B2B marketing with special focus in oil & gas and the energy industries. She helps delivering the best customer experience with GE Digital products and services assisting companies to maximize the value of Asset Performance Management and unlock the potential of software and digitalization. Francis holds a Masters in Integrated Marketing from Northwestern University and is based in the energy capital of the world, Houston, Texas, USA.