This week’s guest on the Hypercube podcast is Anjukan Kathirgamanathan, Senior Data Scientist at GridBeyond. As part of the modelling and forecasting team, Anjukan joins us to talk about machine learning (ML) techniques in the energy space.

Adam and Anjukan take a deep dive into reinforcement learning (RL), a subset of ML. RL enables an agent to learn how to take the optimal set of actions by interacting with a dynamic environment, learning in a similar way to humans. It is an area with great possibilities for the energy space, but there are a number of challenges to overcome—from educating customers to having sector-specific talent. Anjukan shares his perspective as a data scientist working on real-world RL applications.

In this episode, we discussed:

• Human oversight in AI-powered trading.
• Data quality for ML modelling.
• Challenges in deploying RL in practical applications.
• Managing smaller, distributed resources with RL
• Attracting data science talent to the industry.

The weekly Hypercube podcast sits down with leaders in the energy and utilities sectors to explore how data analytics can help businesses make smarter decisions and accelerate business growth.

Chapter Markers

[0:30] Anjukan introduces himself and gives an overview of where GridBeyond sits in the ecosystem.

[3:02] Anjukan explains why pricing is the area of forecasting where he sees the greatest value-add.

[4:31] Adam asks Anjukan to talk more about AI-based control methods and reinforcement learning.

[7:57] Anjukan digs deeper into the topic of reinforcement learning and the challenges of bringing it to market.

[10:59] Adam and Anjukan discuss how to help customers buy-in to reinforcement learning.

[14:41] Anjukan shares his advice for battery owner start-ups interested in adopting AI and reinforcement learning.

[16:57] Anjukan gives his view on the potential for reinforcement learning to be used within the energy industry.

[19:13] Adam asks Anjukan to share his perspective on the talent crunch in AI and reinforcement learning, specifically for the energy sector.

[21:30] Anjukan emphasises multi-agent reinforcement learning in the energy space as an area he thinks will be exciting over the next few years.

[23:00] Anjukan speaks about the technologies he feels are overhyped in the energy space.

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