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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

Frost & Sullivan
2250.0000 USD https://store.frost.com/impact-of-artificial-intelligence-ai-on-energy-and-utilities-2018.html
RELEASE DATE
18-Sep-2018
REGION
Global
Research Code: ME1F-01-00-00-00
SKU: EG01918-GL-MR_22318
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  • Description
  • Infographics
  • Table of Contents
  • List of Figures & Charts
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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

This infographic presents a brief overview of the research, and highlights the key topics discussed in it.
Click image to view it in full size

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 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
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