Track 1: AI-Driven Data Centers: From Massive Electricity Loads to Flexible Energy Resources

Organizers

Additional Co-Chairs and Track Committee members will be invited from leading universities, research institutions, and industry organizations in Vietnam and internationally as the track develops.

Abstract

The rapid development of Artificial Intelligence (AI), cloud computing, and digital services is transforming data centers into some of the fastest-growing and most dynamic electricity loads in modern power systems. The increasing deployment of AI computing infrastructure is not only driving unprecedented electricity demand, but also introducing highly variable and bursty power consumption, creating new challenges for power-system planning, electricity markets, grid operation, power quality, energy security, and decarbonization.

At the same time, the flexibility of computational workloads, together with advances in energy storage and intelligent control, creates an emerging opportunity to transform data centers from passive electricity consumers into controllable and flexible energy resources. This track focuses on the emerging intersection of AI, data centers, energy storage, renewable energy, and future power systems.

The track welcomes research addressing AI-driven data center energy consumption, workload-aware energy management, power capping, workload scheduling, demand response, Battery Energy Storage Systems (BESS), renewable energy integration, electricity-market participation, and grid-interactive data centers. Particular attention is given to AI-based optimization, reinforcement learning, digital twins, forecasting, and intelligent control approaches capable of managing the complex and partially observable operational characteristics of data-center workloads.

The track also seeks contributions exploring how AI data centers can support future smart grids through demand-side flexibility, peak-demand reduction, renewable-energy integration, ancillary services, and coordinated operation with energy storage. Both theoretical and practical contributions, including mathematical modeling, optimization, AI algorithms, simulation, experimental validation, and industrial case studies, are welcome.

Topics of Interest

A. AI-Driven Data Center Energy Systems

• Electricity Consumption of AI and High-Performance Computing Data Centers
• Energy Characteristics of AI Workloads
• Data Center Load Modeling and Forecasting
• Workload-Aware Energy Management
• AI Data Center Power Demand Characterization
• Data Center Energy Efficiency
• Sustainable and Green Data Centers
• Energy-Aware Computing and Resource Allocation
• Data Center Power Capping
• Data Center Thermal and Cooling Energy Management

B. Flexible Data Centers and Smart Grids

• Data Centers as Flexible Energy Resources
• Grid-Interactive Data Centers
• Demand Response for Data Centers
• Flexible Load Management
• Data Center Participation in Electricity Markets
• Peak Demand Management
• Load Shifting and Workload Scheduling
• Data Center Ramping and Flexibility
• Ancillary Services from Data Centers
• Data Centers as Virtual Power Resources

C. AI-Based Energy Management and Optimization

• AI-Based Energy Management Systems
• Reinforcement Learning for Data Center Energy Management
• Deep Reinforcement Learning
• Partially Observable Decision-Making for Energy Systems
• Machine Learning for Energy Optimization
• Multi-Agent Reinforcement Learning
• AI-Based Optimal Scheduling
• Predictive and Adaptive Energy Management
• Digital Twins for Data Centers
• AI-Enabled Predictive Control

D. Energy Storage and Data Centers

• Battery Energy Storage Systems (BESS) for Data Centers
• Coordinated Data Center-BESS Operation
• Battery Scheduling and Energy Arbitrage
• Peak Shaving Using BESS
• Energy Storage for Power Quality Improvement
• Hybrid Energy Storage Systems
• Battery State-of-Charge Management
• Data Center-BESS-Grid Coordination
• Energy Storage for Resilient Data Centers

E. Renewable Energy Integration

• Renewable-Powered Data Centers
• Data Center Integration with Solar and Wind Energy
• Renewable Energy Forecasting
• Data Center-Renewable Energy Coordination
• Renewable Energy Curtailment Reduction
• Carbon-Aware Data Center Operation
• 24/7 Carbon-Free Energy for Data Centers
• Renewable Energy and Energy Storage Co-Optimization
• Data Centers and Net-Zero Energy Systems

F. Power Systems and Electricity Markets

• Impact of AI Data Centers on Power-System Planning
• Large-Load Integration into Power Systems
• Electricity Market Impacts of AI Data Centers
• Locational Electricity Pricing and Data Center Siting
• Power-System Flexibility and AI Loads
• Grid Congestion and Large Data Center Loads
• Power Quality and Power Electronics in Data Centers
• Grid Reliability and Resilience
• Transmission and Distribution Planning for Large Computing Loads
• Data Centers in Future Smart Grids

G. Emerging Technologies

• Generative AI and Energy Systems
• Large Language Models for Energy Management
• Edge AI and Distributed Computing
• AI-Based Predictive Maintenance
• Intelligent Power Electronics for Data Centers
• Data Center Microgrids
• Cyber-Physical Energy Systems
• Digitalization of Data Center Infrastructure
• AI for Energy Transition and Decarbonization
• AI-Powered Grid-Interactive Data Centers

Proposed Invited Speakers (more to be added...)