38 39 1. Repowering generation: Upgrading existing power plants can expand capacity with fewer permitting challenges. For example, upgrading Combined Cycle Gas Turbine (CCGT) components can increase the capacity of gas-fired plants by up to 25%. Build investment-backed programs to identify and coordinate repowering opportunities, incl. labour supply chain & permitting. 2. Delaying retirements: Extending the lifespan of older plants can bridge supply gaps with existing transmission infrastructure. Systematically identify and address retirements that are technically and commercially feasible and within policy preferences. 3. Behind-the-meter integration: Optimizing data centers’ existing assets, such as backup generators, batteries, and solar panels, and improving visibility to grid operators can unlock value for all. Pilot data-sharing protocols and grid participation models. 4. Battery placement: Installation of battery storage at optimal locations on the grid increases capacity and resilience. As curtailment has risen in recent years, California plans to increase its installed battery storage from 16 to 52GW by 2045. Encourage investment-backed program to install new or existing batteries in optimal locations to ease congestion around data center clusters. 5. Transmission lines: Implementing dynamic line ratings based on real-time conditions and dynamic modeling of the grid can increase transmission capacity. Pilot best practice AI-enabled dynamic line rating systems on key transmission corridors to enhance data center grid headroom. 6. Flexible compute: Shifting data center computing tasks in time and space can ease grid pressure and improve flexibility. Pilot compute-shifting frameworks based on grid signals, evaluating cost, emissions and policy needs. 1. New clusters: Developing future data centers away from existing overloaded clusters would reduce the strain on energy infrastructure. Curate a Data Center Readiness Index to benchmark optimal locations for data centers based on criteria such as energy availability, water resources, labor markets, infrastructure suitability, regulatory conditions, connectivity, and climate resilience. 2. Permitting: Streamlining and automating the critical but time- consuming permitting processes would accelerate the build-out of essential energy infrastructure. The US DoE has launched a pilot to develop Permit AI, a tool to expedite federal environmental reviews. Develop a GenAI tools to automate project execution, permit generation and review processes. 3. Upskilling: Regulators require enhanced training to manage increased complexity and pace of the energy build- out. The US DoE highlights an urgent need to expand training beyond traditional fields to ensure workforce is equipped with the skills required in the future. Leverage AI to plot career trajectories, upskill public servants and disseminate best practice. 1. Short-term surge 2. Long-term build-out 7. Consumer load-shifting: Pricing signals, alerts and automation are effective tools to incentivize end users to reduce or shift energy consumption during peak hours. California’s proactive alerts during a heatwave swiftly reduced consumption by 2,100MW. Test behavioral interventions and automation tools to scale demand- side flexibility. 8. Equitable cost allocation: Assigning grid upgrade costs based on share of usage ensures fairness and drives efficient siting. Data centers are expected to account for 40% of new electricity demand by 2040 per our analysis, requiring major investments in transmission infrastructure. Develop frameworks for high-load users to pay proportionate costs through pricing and rate reforms. 9. Humanizing energy: Gamification of energy use can drive and reward consumer behaviors that reduce demand during peak hours or shift it to non-peak hours. AI tools connected to consumers’ smart home devices can optimize energy consumption by adjusting the time when the devices are used based on peak times. 4. New investment models: New commercial models and financial mechanisms are essential to unlock capital for energy infrastructure projects at scale. Develop and assess alternative models to finance the build-out and operation of data center-related energy infrastructure. 5. AI digital twins: Addressing vulnerabilities in aging and complex grid systems through AI can be addressed with AI-enabled design and operations. The US incurs an average of 250 power cuts per year for an average of 5 hours. Create a database of grid disruptions along with an AI tool to identify and prevent disruptions learning from similar events around the world. 6. Predictable data center power: Data centers are a new class of energy user posing unique challenges for grid stability and energy affordability due to their intensive energy use. US data centers are projected to account for up to 18% of the country’s overall electricity usage by 2050. Standards and regulation could play an important role around data center efficiency, design and power consumption (including day-ahead nomination of usage). 7. Efficiency standards: Developing efficiency standards and tools for other sectors is crucial to ensure energy efficiency. For instance, the NREL utilizes integrated energy system simulations to co-optimize across multiple energy systems. Build an integrated energy model to help optimize the energy transformation, minimizing capital, resources, energy and carbon intensity. 8. Open innovation: AI has the potential to accelerate innovation related to energy and materials. For instance, new research suggests that High Performance Computing and AI can accelerate the path toward commercial fusion energy. Identify and develop specific areas, such as batteries, SMRs, and fusion, for investment in open- source innovation. HIGH-IMPACT SOLUTIONS AND NEXT STEPS HIGH-IMPACT SOLUTIONS AND NEXT STEPS 5 5