Artificial Intelligence for Utilities

Live Streaming Online August 1, 2023

An EUCI Program

If you are unable to attend at the scheduled date and time, we make recordings available to all registrants for three business days after the event

Artificial intelligence (AI) adoption has soared in the last decade, enhancing ways utilities can digitize to deliver the best ROI. AI has benefited the industry with new solutions to move from reactive to proactive, to support the digital transformation, to reduce operational costs, improve security and strengthen resilience.

Register now for the very latest on how AI is currently being used in the energy sector, how to get started, and how to ramp up your efforts even more than before. Don’t miss this unique opportunity to get a better understanding of this evolving new technology.

Learning Outcomes

Review the basics of artificial intelligence
- AI – why now?
- AI vs. other technology terms
- What is AI?
- Basic components of AI
- What constitutes an AI algorithm?
- What constitutes an AI model?
- Types of AI
- AI vs. Machine Learning vs. Deep Learning (or Neural Networks)
- What is machine learning?
- Types of machine learning
- What is deep learning?
- Types of deep learning
Assess how AI is currently being used in the Utility Industry
Gain insights on future AI usage in the Utility Industry
Review challenges in AI adoption
Identify how to get started if you are just embarking on your AI journey
Identify how to kick your program in high gear if your program is already in flight
Discuss typical roles on an AI team
Hear the latest on AI Trends and Impacts for Utilities
Develop an understanding of the new data requirements of drones and robotic Inspection Devices
Discover how to boost revenue growth & cost savings with AI
Outline best practices for using AI to optimize production and improve supply chain management

Agenda

TUESDAY, AUGUST 1, 2023

9:00 a.m. – 4:45 p.m. Central Time

9:00 – 11:00 a.m. :: Introduction to AI Usage within the Utilities Industry

In this session attendees will learn what AI is, how it works, and how it’s being used in the utility industry to help companies reduce costs, increase profits, and improve overall performance.

Overview of Robotic Process Automation and Artificial Intelligence – Why are They Typically Intertwined?
Artificial Intelligence in the Utilities industry:
- How is it currently being used
  - Predictive Maintenance
  - Grid Optimization
  - Energy Management
  - Cybersecurity
  - Autonomous Vehicles
  - Natural Language Processing
- Future AI Usage in the Utility Industry
  - Renewable Energy Integration
  - Energy Store Management
- How to get started with AI

Jack Dowling, President and CEO, VOTUM Technology Group

11:00 – 11:15 a.m. :: Morning Break

11:00 a.m. – 12:30 p.m. :: AI Trends & Impacts for Utilities

Big Data, IoT, Enterprise Data Management and the New Data Requirements of Drones and Robotic Inspection Devices

This session begins with key industry/societal trends and their impacts. To realize greater benefits from Intelligent Electronic Devices (IEDs) the two types of data within the IED, operational and non-operational, must be managed differently. The Internet of Things (IoT) and its benefits, and examples of new groups of analytics being developed, will be discussed. The importance of convergence of the Operations Technology and Information Technology groups within a utility will be emphasized, and its enablement of enterprise data management. Grid modernization industry standards are critical for success in the facilitation of integration and interoperability. The journey to digital transformation will be discussed and how greater use of artificial intelligence, machine learning, and the digital twin can accelerate the journey from reactive to predictive to autonomous. Lastly, the use of new sources of data – unmanned aerial vehicles (UAVs) and robotics – will be described and data management principles will be discussed.

John D. McDonald, P.E., Smart Grid Business Development Leader at GE Vernova Grid Solutions

12:30 – 1:00 p.m. :: Lunch Break

1:00 – 2:15 p.m. :: Case Study: How to Boost Revenue Growth and Cost Savings with AI

AI tools like ChatGPT have become an overnight sensation, exposing the power of generative AI tools to the entire world. CEOs and CFOs are asking how they can take advantage of new AI tools such to radically improve company performance. Learn how Entergy formed an AI Task Force to tackle this challenge, including assessing AI’s potential business uses, risks, organizational impacts, and human resources considerations. Discover what high-impact utility business cases might be pursued leveraging AI tools, how to identify and evaluate various risks associated with adopting AI tools at scale, how to educate people in AI technologies, and discover what AI is (and is not).

Andy Quick, Vice President at Business Data and Insights, Entergy

2:15 – 2:30 p.m. :: Afternoon Break

2:30 – 4:15 p.m. :: Grid Optimization through AI with Increasing DER Penetrations

Energy companies can leverage AI to enhance operations and security. In this session we will outline best practices for using AI to optimize production and improve supply chain management. Increasing amounts of DER complicates grid operation, especially for distribution grid operators. This session will cover:

Growth of DER integrations
Operational challenges on distribution grids
How AI can potentially help
Potential risks: reliability, affordability and cybersecurity
Emerging open source tools

Bo Yang, Senior Director, Power/Energy, Hitachi America, Ltd.

4:15 – 5:00 p.m. :: Responsible AI – Reflecting on the ethical side of AI

Artificial intelligence is heavily trending today – it’s the beginning of a new era. From autonomous driving to immersive shopping, from smarter video collaboration in today’s hybrid world to generative AI, technology is bringing it all at our fingertips. However, there are many vulnerabilities while using AI and the cost we pay for such AI accidents is huge, from amplifying historical biases to making decisions that we cannot interpret. With the rise of AI-based solutions, the need for us to understand the motivation behind these black-box models is imperative. We will explore real scenarios that show the perils of using AI in the wild. Learn how these risks can be addressed using various techniques throughout the model development and deployment process and recognize how to develop best practices in taking AI products to market.