The Digital Energy Transformation

Change is being driven by three powerful trends: the emergence of digital technologies, the arrival of increasingly affordable distributed power technologies, and decarbonization through the maturation of renewable energy and energy efficiency options.
Contact Us

Digitalization

The Industrial Internet of Things (IIoT) opens up a range of applications and potential for optimization across industries.
For electricity, in particular, IIoT applications have been developed to:
  • operate and control T&D networks
  • improved the performance of individual and fleets of power
  • optimize hybrid microgrid systems

Decentralization

GE has long recognized, encouraged, and contributed toward the trend of smaller, decentralized power systems that meet on-site electricity needs.
  • Their small size and dependability make them the generator of choice.
  • They're able to meet the heating, cooling, or steam needs of end-users.
  • They enable distributed power systems to store energy from variable generation sources and discharge at periods of peak demand.

Decarbonization

Climate change is an imminent and serious threat that can be addressed through decarbonization of the global energy system.
  • Policies have been implemented in the last two decades which have led to sustained decarbonization of the global electricity system.
  • 42 percent of global carbon dioxide emissions come from the global electricity system.
  • The result of both policy push and innovation pull toward decarbonization has been the rapid growth of renewable energy technologies.

The Digital Energy Journey

From a fledgling industry near the turn of the twentieth century, electricity has become an integral part of society, commerce, and technology, and we expect electricity to play an increasingly important role in the future as digital technologies become increasingly prevalent.

Industrial
Timeline

Power
Plants

Wind
Farms

Digital
Grid

AI/Machine
Learning

Block
Chain

Digitization
Benefits

Road
Ahead

MENU

Industrial Internet Timeline

Industrial software systems have evolved over the last 50 years from monolithic systems that provided machine-level control, to today’s Industrial Internet, which facilitates resource optimization for global industrial networks.

  • Monolithic
  • Distributed
  • Networked
  • Industrial Internet

1950s - 1960s

Monolithic

Enabled Machine-Level
Resource Optimization

The first generation of industrial control software used large mini-computers connected to industrial machines with no connectivity to other systems. They had limited security.

1950

1960

1959
Texaco’s Port Arthur refinery becomes the first chemical plant to use digital control.

1970s - 1980s

Distributed

Enabled Facility-Level
Resource Optimization

The second generation of industrial control software was distributed across multiple independent workstations connected through proprietary communications protocols. They had limited security.

1970

1980

1969
The first nodes of what will become the Advanced Research Projects Agency Network (ARPANET) are established. ARPANET was the precursor to today’s internet.
1982
The Internet protocol (TCP/IP) is established. This standard enabled seamless communication between interconnected networks.
1985
The number of hosts on the Internal (all TCP/IP interconnected networks) reaches 2,000.

1990s - 2000s

Networked

Enabled Enterprise-Level
Resource Optimization

The third generation of industrial control software were distributed and networked, and computers could be interconnected through a secure local area network (LAN). The systems spread across multiple LANs and across geographies.

1990

2000

1990
The Internet grows to over 300,000 hosts.
1991
After the ARPANET project was concluded, all commercial restrictions on the use of the Internet are removed.
1994
The concept of the Internet of Things (IoT) is first developed. The basic idea was to affix sensors to common objects in order to connect these items to the Internet.
1999
The Massachusetts Institute of Technology (MIT) establishes the Auto-ID Center to conduct research focused on IoT. During the same year, the world’s first machine-to-machine protocol, MQ Telemetry Transport (MQTT), is developed.
2008
The first international IoT conference takes place in Zurich.

2010s - Today

Industrial Internet

Enables Global Network
Resource Optimization

Over the last decade, cloud computing, network bandwidth increases, hardware improvements, and software advances have enabled the emergence of the Industrial Internet.

2010

2020

2010
The number of Internet hosts exceeds 800 million.
Improvements in information technologies enabled the IoT to be applied to industrial machinery.
2012
GE announces its commitment to a $1 billion investment in software and analytics and launches the Software and Analytical Center of Excellence in California.
2013
GE develops the first software platform for the Industrial Internet.
2014
GE’s portfolio grows to 31 Industrial Internet applications within its Predictivity suite of solutions. The Industrial Internet Consortium is established to further the development, adoption, and widespread use of the Industrial Internet.
2015
GE releases an operating system for the Industrial Internet. GE’s cloud-based platform is designed for building and powering Industrial-strength applications.
2015
GE and Intel joined forces in order to leverage the power of ICT to help solve the world’s toughest global natural resource challenges.
2016
Intel scales its architecture for IoT through a wide range of product offerings. Intel® Quark™, Intel Atrom™, Intel Core™, and Intel Xeon® processors each support a wide range of performance points with a common set of code, analytics, encryption, and new application requirements in IoT.
Intel announces the availability the Intel Building Management Platform to help small- and medium-size buildings become smart and connected.
Source: (Owens, Digital Resource Productivity 2014)

Industrial
Timeline

Power
Plants

Wind
Farms

Digital
Grid

AI/Machine
Learning

Block
Chain

Digitization
Benefits

Road
Ahead

MENU

GE’s Digital Power Plant

GE’s Digital Power Plan (DPP) showcases an agile digital infrastructure and a suite of innovative digital applications built for the IIoT.

Operations
Optimization
Business
Optimization

Asset Performance

Advanced predictive analytics improve plant reliability and availability, allowing plants to diagnose root cause and corrective actions more quickly.
Asset
Performance
Business
Optimization

Operations Optimization

Visualizing startup details, including fuel consumption, emissions, and start costs; aligning operating profiles with marketplace dispatch needs; and diagnosing thermal system performance and reducing cycle losses allow for beneficial operations optimization.
Asset
Performance
Operations
Optimization

Business Optimization

Weather forecasts and tuned plant models can be sued to respond to marketplace price signals.

Digital Gas and Steam Power Plants

Given the size of the global power fleet and the important role that electricity generation plays within the global energy value chain, the potential impact of digital technologies on power generation assets and systems has the potential to provide significant economic and environmental benefits.

There are three focus areas for power plant digital applications:

Operations performance management (OPM)

Operations performance management (OPM):

Increasing power plant efficiency, capacity, and flexibility through improvements in operations performance.

Asset performance management (APM)

Asset performance management (APM):

Optimizing asset strategies, improving machine and equipment health, and improving reliability through performance management.

Field service management

Field service management:

Reducing operations and management costs through better demand and technician planning.
Source: GE Power (Our Air page 26)

Industrial
Timeline

Power
Plants

Wind
Farms

Digital
Grid

AI/Machine
Learning

Block
Chain

Digitization
Benefits

Road
Ahead

MENU

Digital Wind Farms

The drive to decarbonize the global power system and startling improvements in renewable energy technologies have ushered in the renewable energy era.

One of the most interesting digital solutions is a suite of applications designed to improve the performance of wind turbines while reducing O&M costs, extending asset life, and reducing unplanned downtime.

Analytics and optimization

GE Renewable Energy’s Wind Farm solution extends analytics and optimization beyond a single wind turbine to the entire wind farm.

Dynamic wind energy platform

GE Renewable Energy harnessed the power of the emerging IIoT to create the Digital Wind Farm, a dynamic, connected, and adaptable wind energy platform that pairs wind turbines in a wind farm with digital infrastructure to optimize efficiency across the entire wind farm.

Optimize wind plants at turbine level

This platform can account for the wind farm’s topology, surrounding geography, wake effects, and other inputs to control individual wind turbines and optimize the operation as a whole.

Through these techniques, the Digital Wind Farm technology boosts a wind farm’s energy production by up to

20%

and could help generate up to an estimated

US$50 billion

value for the wind industry.

Source: (Owens, Hydropower’s Digital Transformation 2017)

Industrial
Timeline

Power
Plants

Wind
Farms

Digital
Grid

AI/Machine
Learning

Block
Chain

Digitization
Benefits

Road
Ahead

MENU

The Digital Grid

As power networks evolve to include more distributed energy resources, electricity production is shifting towards a larger share of decentralized and renewable energy sources.

Stress on the grid

This increase in distributed energy resources is creating stresses on the grid. The move toward decentralization has introduced the need to increase the levels of bi-direction electricity flows on networks, is creating more voltage fluctuations, and is increasing the volatility of power production and local network congestions.
Digital
Technologies
Digital
Transformation

Digital Tools

Digital tools have long been used to help manage and operate the grid. Existing digital tools range from protection relays and substation controllers in the periphery, to power plant controls, and all the way up to utility energy management platforms in the operation centers.
Digital
Tools
Digital
Transformation

Digital Technologies

The smart pairing of these emerging digital technologies with the conventional physical and digital tools already available in the grid creates an opportunity to transform global T&D systems to deliver important outcomes such as:
  • Improved reliability
  • Improved ability to integrate greater levels of renewable energy resources
  • Enhanced utilization of existing and new infrastructure, and hence better economic returns
Digital
Tools
Digital
Technologies

Digital Transformation

The digital transformation of transmission and distribution systems is a long journey that will first take utilities from a reactive mode of operation to a predictive and even prescriptive framework. This will allow operators to make faster decisions, which will enable a more dynamic and efficient management of the grid. In the longer term, as artificial intelligence and machine learning progress, human intervention in the daily grid operations is expected to decrease, giving way to a fully-automated or autonomous management of the grid.

Industrial
Timeline

Power
Plants

Wind
Farms

Digital
Grid

AI/Machine
Learning

Block
Chain

Digitization
Benefits

Road
Ahead

MENU

Artificial Intelligence & Machine Learning

Artificial intelligence (AI) and machine learning (ML) are technologies that could help compress and analyze the massive amounts of data that the energy industry produces so our human decision-making would not be overwhelmed by the explosion of data.

Use Cases

There are many different use cases of AI and ML in the energy industry.

These include machines that:

Learn on their own from spotting patterns & anomalies in large data sets.
Use AI technology to reduce its total data center power consumption.
Use AI and ML to determine the best generation mix.

This will revolutionize both the demand and supply side of the whole energy economy.

GE has employed artificial intelligence in many aspects of its “Digital Twin,” a digital solution that provides a software representation of any physical asset such as a power plant or an aircraft.

AI is augmenting the Digital Twin through:

Pattern Recognition

Contributing to developing the behavioral Digital Twin of an asset by using various sources of measurement data collected over time.

Learning Models

Unstructured Data Analysis

Multimodal Data Analytics

Knowledge Networks

Pattern Recognition

Learning Models

Modeling platform within which twins of assets are continuously created, validated, monitored, and updated at a speed close to real-time.

Unstructured Data Analysis

Multimodal Data Analytics

Knowledge Networks

Pattern Recognition

Learning Models

Unstructured Data Analysis

Addressing the massive amounts of unstructured data that enterprises must deal with in the lifecycle of a part and asset.

Multimodal Data Analytics

Knowledge Networks

Pattern Recognition

Learning Models

Unstructured Data Analysis

Multimodal Data Analytics

Predicting failures and maintaining automated, live, up-to-date asset health scores usually requires data from multiple modalities.

Knowledge Networks

Pattern Recognition

Learning Models

Unstructured Data Analysis

Multimodal Data Analytics

Knowledge Networks

Leveraging digital platforms to quickly connect experts as well as observe how modeling and analytical tools are used to develop Digital Twin models and supporting systems.

Industrial
Timeline

Power
Plants

Wind
Farms

Digital
Grid

AI/Machine
Learning

Block
Chain

Digitization
Benefits

Road
Ahead

MENU

Blockchain

Blockchain technology has gained significant levels of attention across several industries and is believed to be a disruptive technology by many thought leaders.

Backbone
Technology
Future Utility
Platform

What is it?

At its core, Blockchain technology is a ledger that is shared, replicated, and distributed. It can be used to manage and record transactions across multiple network participants, on which the transactions can be triggered based on predefined conditions. It can also eliminate the need for an additional layer of centralized information validation and all the additional costs and processes that come with centralized systems.
What
Is it?
Future Utility
Platform

Backbone Technology

These core characteristics of Blockchain technology seem to be well-fit to accelerate the digitalization, decarbonization, and decentralization trends transforming the energy industry. Blockchain has the potential to become a backbone technology that provides additional data security, integrity, efficiency, and productivity to the IIoT. Through a single source of truth ledger, it could eliminate the need for reconciliations and facilitate more efficient, cost-effective, and intelligent transactions.
What
Is it?
Backbone
Technology

Future Utility Platform

As the current utility business model is being reimagined, Blockchain technology is being considered as an enabler of the future utility platform. It could enable the creation of an open marketplace to orchestrate in real-time the many energy sources and loads, including electric vehicles, energy storage, intermittent renewable energy, and microgrids.

Industrial
Timeline

Power
Plants

Wind
Farms

Digital
Grid

AI/Machine
Learning

Block
Chain

Digitization
Benefits

Road
Ahead

MENU

The Benefits of Digitalization

Taken together, the potential energy, economic, and environmental benefits of the digitalization of electricity are enormous. GE and others have assembled some initial estimates of the scale of these benefits.

“Digital solutions in the power industry can create over US$2 trillion dollars from the reduction in greenhouse gas emissions, new job creation, and value for consumers.”

  • Economic
  • Environmental

Economic Benefits of Energy Digitalization

As discussed, the potential economic benefits of energy digitalization are significant. According to the World Economic Fourm, the value stream to the power industry for service platforms, smart devices, and advanced analytics is US$1.3 trillion. Asset performance management solutions alone have the potential to create value by lowering operations costs and eliminating unplanned downtime. Digital solutions in the power industry can create over US$2 trillion dollars from the reduction in GHG emissions, new job creation, and value for consumers.
Source: (World Economic Forum January 2016)
Even more broadly, the global e-Sustainability Initiative recently found that an IIoT-enabled world could be cleaner, smarter, and more prosperous. They estimated that ICT could bring about a 20 percent reduction in global carbon dioxide emissions by 2030 through the application of Internet-enabled solutions. This would also reduce costs by US$4.9 trillion by 2030, with US$1.2 trillion in reduced electricity expenditures, and US$1.1 trillion in reduced fuel expenses.
Source: (GESI 2015)

GE’s Digital Power Plant Benefits

Consider GE’s Digital Power Plant (DPP), a suite of digital applications that improve the performance of power plants and reduce asset downtime using cloud-based analytics on GE’s Digital platform. If DPP solutions were to be installed across the global fleet of coal and gas-fired power plants, carbon dioxide emissions from power plants would be reduced by 10 percent. As discussed, recent GE analysis also suggests that if digital grid technologies are fully deployed globally, electricity consumption could be reduced by as much as 12 percent and carbon dioxide emissions could be reduced by 2 billion metric tons by 2030.
Source: (de Bedout and Owens 2017)

Industrial
Timeline

Power
Plants

Wind
Farms

Digital
Grid

AI/Machine
Learning

Block
Chain

Digitization
Benefits

Road
Ahead

MENU

The Road Ahead

Despite the potential and early success of energy digitalization efforts, there remains several challenges that must be overcome in order to unlock the full potential of our digital energy future:

Encourage Adoption

Early digital energy adoption needs to be encouraged. As with all technological innovation, many stakeholders initially resist adoption because of the perceived risks involved, up-front costs, and uncertainty around positive outcomes. Given the tremendous economic and environmental benefits of energy digitalization, policymakers and regulators may want to consider both financial incentives and digital technology requirements that compel industry to begin their digital transformation.

Advance Digital Energy R&D

Privacy and Security

Cybersecurity

Cultivate Talent

Encourage Adoption

Advance Digital Energy R&D

Industry, government, and universities must advance digital energy R&D. Industry participants have moved forward with a wide array of digital energy pilot projects. These projects should not only be encouraged but also supplemented by public research dollars that enable market participants to verify the positive outcomes of energy digitalization.

Privacy and Security

Cybersecurity

Cultivate Talent

Encourage Adoption

Advance Digital Energy R&D

Privacy and Security

Data privacy and security concerns need to be successfully addressed. A major barrier to the increased use of digital technologies in the energy arena is industry and public concerns about data privacy and security. Energy use, cost, and production data are highly sensitive, and the risk of data loss or theft as a result of increased connectivity is a disincentive for companies as they attempt to embrace digitalization.

Cybersecurity

Cultivate Talent

Encourage Adoption

Advance Digital Energy R&D

Privacy and Security

Cybersecurity

Cybersecurity needs to be increased. The digitalization of energy infrastructure opens the door to increased risks for energy security from both unintended cyber incidents and intentional cyber-attacks. Today, there is an ever-increasing threat landscape for energy infrastructure.

Cultivate Talent

Encourage Adoption

Advance Digital Energy R&D

Privacy and Security

Cybersecurity

Cultivate Talent

Talent should be cultivated. Digitalization will require new talent pools to be created and grown. Beyond the obvious technical skills in mechanical or electrical engineering, there will be a need for a wave of new technical, analytical, and leadership roles that are explicitly cross-discipline in nature.

World Energy Innovation Leaders

The digitalization of energy will be the defining feature of twenty-first-century energy systems. We’re committed to building a world-class industrial software and analytics capability and have accelerated the digitalization of all GE solutions through the development of digital platforms.
Our digital future has just begun. Contact us to learn how you can take part in it.
Contact Us
Download the full whitepaper below.
Download Whitepaper