For many countries in Asia, pathways to clean energy transitions are complex with continued reliance on coal and legacy infrastructure, a rapidly urbanising economy, and a booming data centre industry. How can we ensure that AI adoption is both safe and sustainable while also fostering equitable energy transitions? 

In this episode, we hear from John Cotton & Priya Donti on the enthusiasm of governments in Asia in using AI to improve the efficiency of energy systems & manage energy demand & supply. We discuss AI’s potential to help integrate renewable energy sources into the grid, challenges in the area, environmental impacts & ways to manage them, and the need to invest in capacity building & skill development.

You can read the transcript for this episode ⁠here.

Speakers

John Cotton 

John Cotton is Senior Program Manager for the Southeast Asia Energy Transition Partnership, UNOPS with a demonstrated history of project development in energy transition, renewables, IT and mining industries. John is educated in the UK at Manchester and Sussex Universities with a B.Sc (Hons) in Mathematics, Software Engineering, and an M.Sc in Energy Policy, respectively.

John has been based in Southeast Asia for 20 years and has overseen projects ranging from EPC contracts for hydropower and solar projects, through policy analysis and recommendations for the multi-disciplinary energy transition challenges faced across the region. Before ETP, he was Climate Change Policy Officer at the British Embassy, Vientiane of Lao PDR, and draws on extensive experience from both the public and private sectors.

Priya Donti

Priya Donti is an Assistant Professor at MIT EECS and LIDS, whose research focuses on machine learning for forecasting, optimisation, and control in high-renewables power grids. Specifically, her work explores methods to incorporate the physics and hard constraints associated with electric power systems into deep learning workflows. 

Priya is also the co-founder and Chair of Climate Change AI, a global non-profit initiative to catalyse impactful work at the intersection of climate change and machine learning. She received her Ph.D. in Computer Science and Public Policy from Carnegie Mellon University.

Show Notes

COP26: What Asia pledged, from China to Vietnam and Philippines

PT PLN  Indonesia’s State Utility Company

A comprehensive overview on demand-side energy management towards smart grids: challenges, solutions, and future direction

Upgrading and Modernising the Java-Madura-Bali Electricity Control Centre

Renewable Integration - Energy System - IEA

Development of Vietnam Smart Grid Roadmap for period up to year 2030, with a vision to 2050

Review on Machine Learning for Sustainable Energy Systems

Aligning artificial intelligence with climate change mitigation (overview of the multi-faceted relationship between AI and climate)

Climate Change and AI: Recommendations for Government Action (Global Partnership on AI report)

French grid operator RTE

Learning to Run a Power Network challenge

SCADA/EMS

Electricity 2024 – Analysis - IEA

What Are Renewable Energy Certificates (RECs)?

Global Brands Say Future Orders at Risk Given Cambodia’s Increasing Coal Power

UNFCCC (United Nations Framework Convention on Climate Change)

Microsoft deal propels Three Mile Island restart

Tiny machine learning

OpenSynth - LF Energy

Check out the Code Green glossary for more terms.

This podcast series is accompanied by a monthly newsletter - sign up for updates ⁠⁠here⁠⁠. For more about this project, visit our website ⁠⁠codegreen.asia

Credits

Audio Editing: Creator Studio Goa by Winfluence Media

Production Support: Shivranjana Rathore,  Tammanna Aurora,  Dona Mathew,  Meredith Stinger

Cover Design: Nayantara Surendranath

Attributions

Intro and Outro: ⁠⁠Retro Sounds⁠⁠, ⁠⁠Alban_Gogh⁠⁠

Transitions - ⁠⁠Meditative Background Music⁠⁠, ⁠⁠white_records⁠