A Techno-Economic Assessment of Hybrid Renewable Energy and Battery Storage Systems for Data Centers

Abstract

As the demand for data centers continues to grow, so does their energy consumption, making it increasingly important to develop sustainable and cost-effective strategies for powering them with carbon-free electricity. This thesis explores a techno-economic modeling framework that evaluates combinations of solar, wind, and battery energy storage systems to assess their ability to meet a data center’s electricity demand with on-site renewable generation. The model fills a gap in current literature by focusing on real-time energy matching using co-located infrastructure, rather than traditional off-site procurement methods like power purchase agreements and renewable energy credits.

Using real-world weather and price data, the simulation calculates hourly generation, storage behavior, and grid interactions across a 20-year period. A financial model then calculates the levelized cost of energy (LCOE) for each system configuration. Results show that wind energy generally provides the lowest-cost renewable supply option, while hybrid solar and wind configurations improve renewable penetration. Battery storage plays a key role in shifting excess generation to periods of undersupply, but its economic viability depends on system sizing. Across different system configurations, renewable penetration ranged from 31.3% to 97.8%, while LCOE varied from $27.5/MWh to over $100/MWh, illustrating the trade-offs between cost and grid independence.

By providing a structured analysis of the trade-offs between renewable penetration and cost, this research offers insight into how data centers and other energy-intensive facilities can design dedicated carbon-free energy systems. The findings underscore the importance of balancing resource diversity and storage investment to achieve decarbonization goals while maintaining economic viability.