Data center clusters face complex planning challenges that extend beyond simple capacity sizing. The timing and sequence of infrastructure investments directly influence both economic efficiency and grid stability, particularly as load demand grows unpredictably over multi-year horizons. Premature capacity deployment locks in stranded assets, while delayed investments risk service interruptions and system stress during peak demand periods.
This research addresses these competing pressures through a sophisticated multi-stage optimization framework. The methodology begins by characterizing representative operating scenarios across all four seasons, capturing the diversity of power demand patterns throughout the year. This granular temporal resolution improves forecast accuracy and identifies seasonal vulnerabilities.
The planning model then aligns regional energy supply cycles with projected data center load trajectories, enabling coordinated expansion of both generation capacity and grid infrastructure. A tiered carbon trading mechanism embedded within the optimization algorithm reflects realistic carbon markets, where constraint intensity drives technology selection and deployment schedules. By minimizing total lifecycle costs while respecting carbon reduction requirements, the method quantifies the economic impact of climate commitments.
The framework evaluates multiple scenarios with varying carbon constraint levels, revealing how different policy intensities reshape investment decisions. Results demonstrate that the coordinated approach successfully prevents both premature overbuilding and future capacity shortages, while systematically reducing carbon intensity as environmental constraints tighten.
For grid operators and data center developers, this work provides decision-support tools for infrastructure planning that balance reliability, economics, and sustainability. The methodology scales to large, geographically distributed cluster deployments and accommodates diverse generation technologies. As data center demand continues accelerating globally, source-load coordination emerges as essential practice for resilient, cost-effective, low-carbon expansion.
