Impact of Artificial Intelligence (AI) on Energy and Utilities, 2018

Impact of Artificial Intelligence (AI) on Energy and Utilities, 2018

Technology Convergence of AI with IoT, Cloud, and Big Data will Open Up Numerous Application Opportunities in the Energy Sector

RELEASE DATE
18-Sep-2018
REGION
Global
Research Code: ME1F-01-00-00-00
SKU: EG01918-GL-MR_22318
$3,000.00
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Description

Artificial Intelligence (AI) is one of the biggest technological trends transforming every business sector across the world. With advances in computer technology, AI has scaled new heights in utility and application, exceeding all initial expectations. By leveraging advanced machine learning (ML) and deep learning (DL) algorithms, and advanced neural networks (ANN), AI can handle terabytes of structured, semi-structured, and unstructured data from disparate sources and identify patterns, as well as make predictions and recommendations based on its understanding of the data. This intelligence is being harnessed to develop innumerable smart applications that can efficiently take critical decisions autonomously and accurately, without human intervention.

Currently, the global energy market is undergoing a massive shift with the emergence of decarbonisation, decentralisation, and new technologies. Utilities, independent power producers (IPPs), and other energy companies are exploring effective ways to manage the imbalance in demand and supply caused by the growing use of unpredictable renewable energy source (RES) in power generation. Therefore, utilities, energy companies, and grid operators are exploring ways to employ AI technologies to improve the accessibility and efficiency of renewable energy technologies. Despite its nascence, AI possesses tremendous potential to transform the energy & utilities sector. In combination with other technologies like Big Data and IoT, it can aid the active management of electricity grids by balancing demand and supply.

This market insight provides a detailed analysis of the current and future applications of AI in the energy & utilities sector, across the entire energy industry value chain.

The study includes the following:
• Technology trends, which includes AI, its evolution, and the different disciplines in which it is being used
• Industry trends, which includes the application of AI across different business verticals, with use cases
• Geographical adoption and key companies that dominate the global AI market
• The applications of AI across the three main application segments of renewables management, demand management, and infrastructure
anagement

The case studies provide an overview of the current challenges in certain areas of the industry and showcase the ways in which AI can be a better solution than manual methods.

RESEARCH: INFOGRAPHIC

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Table of Contents

AI—Summary of Main Technologies, Solutions, and Benefits

AI—Challenges the Technology can Solve

AI—Maturity of Technologies/Applications

Research Aim & Scope

Research Methodology

Overview of AI

Current and Evolving AI Disciplines

Four Main Layers of an AI System

AI Empowers and Enhances Machine Efficiency

Key Trends Driving the Global AI Industry

AI Technology—Key Challenges

Spectrum of AI Systems

Current Applications of AI across Different Business Verticals

AI Value Chain

Key Stakeholders in AI Value Chain

Global AI Adoption

Key Players in the AI Industry

AI Adoption in Industries

AI Use Cases across Industries

AI Technology Roadmap

AI in Energy & Utilities

Three Main Applications of AI in Energy & Utilities

AI in Renewables Management

Use Case 1—GE: AI in Renewable Energy Management

Use Case 2—NEXTracker: AI in Renewable Energy Management

Use Case 3—Xcel Energy: AI in Renewable Energy Management

Use Case 4—Nnergix: AI in Renewable Energy Management

Other Companies

AI in Demand Management

Use Case 1—Upside Energy: AI in Demand Management

Use Case 2—Hazama Ando: AI in Demand Management

Use Case 3—Origami Energy: AI in Demand Management

Use Case 4—Dexma: AI in Demand Management

Other Companies

AI in Infrastructure & Assets Management

Use Case 1—DeepMind: AI in Infrastructure Management

Use Case 2—Verdigris: AI in Infrastructure Management

Other Companies

Growth Opportunity—AI in Energy

Strategic Imperatives—AI in Energy

Three Big Predictions

Legal Disclaimer

List of Exhibits

List of Figures
  • 1. AI: Key Challenges, Global, 2018
List of Charts
  • 1. AI: Maturity of Technologies, Global, 2018
  • 2. AI: Impact of AI, Global, 2018
  • 3. AI: Current & Evolving AI Disciplines and Techniques, Global, 2018
  • 4. AI: Layers of AI, Global, 2018
  • 5. AI: Impact of Key Trends, Global, 2018
  • 6. AI: Spectrum of AI Systems, Global, 2018
  • 7. AI: Distribution of Patents, Global, 2016
  • 8. AI: Level of Adoption in Businesses, Global, 2018
  • 9. AI: Use Cases across Industries, Global, 2018
  • 10. AI: Technology Roadmap, Global, 2018–2025
  • 11. AI: Current Applications in Renewables Management, Global, 2018
  • 12. AI: Current Applications in Demand Management, Global, 2018
  • 13. AI: Current Applications in Infrastructure & Assets Management, Global, 2018
Related Research
Artificial Intelligence (AI) is one of the biggest technological trends transforming every business sector across the world. With advances in computer technology, AI has scaled new heights in utility and application, exceeding all initial expectations. By leveraging advanced machine learning (ML) and deep learning (DL) algorithms, and advanced neural networks (ANN), AI can handle terabytes of structured, semi-structured, and unstructured data from disparate sources and identify patterns, as well as make predictions and recommendations based on its understanding of the data. This intelligence is being harnessed to develop innumerable smart applications that can efficiently take critical decisions autonomously and accurately, without human intervention. Currently, the global energy market is undergoing a massive shift with the emergence of decarbonisation, decentralisation, and new technologies. Utilities, independent power producers (IPPs), and other energy companies are exploring effective ways to manage the imbalance in demand and supply caused by the growing use of unpredictable renewable energy source (RES) in power generation. Therefore, utilities, energy companies, and grid operators are exploring ways to employ AI technologies to improve the accessibility and efficiency of renewable energy technologies. Despite its nascence, AI possesses tremendous potential to transform the energy & utilities sector. In combination with other technologies like Big Data and IoT, it can aid the active management of electricity grids by balancing demand and supply. This market insight provides a detailed analysis of the current and future applications of AI in the energy & utilities sector, across the entire energy industry value chain. The study includes the following: • Technology trends, which includes AI, its evolution, and the different disciplines in which it is being used • Industry trends, which includes the application of AI across different business verticals, w
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Table of Contents | Executive Summary~ || AI—Summary of Main Technologies, Solutions, and Benefits~ || AI—Challenges the Technology can Solve~ || AI—Maturity of Technologies/Applications~ | Research Scope & Methodology~ || Research Aim & Scope~ || Research Methodology~ | Technology Status, Trends, and Business Models~ || Overview of AI~ || Current and Evolving AI Disciplines~ || Four Main Layers of an AI System~ || AI Empowers and Enhances Machine Efficiency~ || Key Trends Driving the Global AI Industry~ || AI Technology—Key Challenges~ || Spectrum of AI Systems~ || Current Applications of AI across Different Business Verticals~ || AI Value Chain~ || Key Stakeholders in AI Value Chain~ || Global AI Adoption~ || Key Players in the AI Industry~ || AI Adoption in Industries~ || AI Use Cases across Industries~ || AI Technology Roadmap~ | AI in Energy & Utilities~ || AI in Energy & Utilities~ || Three Main Applications of AI in Energy & Utilities~ || AI in Renewables Management~ || Use Case 1—GE: AI in Renewable Energy Management~ || Use Case 2—NEXTracker: AI in Renewable Energy Management~ || Use Case 3—Xcel Energy: AI in Renewable Energy Management~ || Use Case 4—Nnergix: AI in Renewable Energy Management~ || Other Companies~ | AI in Demand Management~ || AI in Demand Management~ || Use Case 1—Upside Energy: AI in Demand Management~ || Use Case 2—Hazama Ando: AI in Demand Management~ || Use Case 3—Origami Energy: AI in Demand Management~ || Use Case 4—Dexma: AI in Demand Management~ || Other Companies~ | AI in Infrastructure Management~ || AI in Infrastructure & Assets Management~ || Use Case 1—DeepMind: AI in Infrastructure Management~ || Use Case 2—Verdigris: AI in Infrastructure Management~ || Other Companies~ | Growth Opportunities & Companies to Action~ || Growth Opportunity—AI in Energy~ || Strategic Imperatives—AI in Energy~ | The Last Word~ || Three Big Predictions~ || Legal Disclaimer~ | Appendix~ || List of Exhibits~ | The Frost & Sullivan Story~
List of Charts and Figures 1. AI: Key Challenges, Global, 2018~| 1. AI: Maturity of Technologies, Global, 2018~ 2. AI: Impact of AI, Global, 2018~ 3. AI: Current & Evolving AI Disciplines and Techniques, Global, 2018~ 4. AI: Layers of AI, Global, 2018~ 5. AI: Impact of Key Trends, Global, 2018~ 6. AI: Spectrum of AI Systems, Global, 2018~ 7. AI: Distribution of Patents, Global, 2016~ 8. AI: Level of Adoption in Businesses, Global, 2018~ 9. AI: Use Cases across Industries, Global, 2018~ 10. AI: Technology Roadmap, Global, 2018–2025~ 11. AI: Current Applications in Renewables Management, Global, 2018~ 12. AI: Current Applications in Demand Management, Global, 2018~ 13. AI: Current Applications in Infrastructure & Assets Management, Global, 2018~
Author Swagath Navin Manohar
Industries Energy
WIP Number ME1F-01-00-00-00
Is Prebook No
GPS Codes 9301-A4,9597,9851,9852,9A33,9AFE-A4,9AFF-A4,9B00-A4,9B07-C1,GETE