LEEDS SUSTAINABILITY CASE COMPETITION
In February, my team won the 2025 Leeds Sustainability Case Competition with our renewable energy procurement strategy for a GenAI company, outperforming 38 teams from 22 schools. Our solution included site selection, PPAs, and energy efficiency measures for hyperscale and edge data centers.
Client: Perimas Technology (not a real company)
Industry: GenAI
Advisors:
Paul Endresen, GenAI Expert, CEO/CTO at 3LC.AI
Josh Radoff, Renewable & Sustainable Energy Specialization Lead at the Masters of the Environment (MENV) Program, CU Boulder
Timeline: December 2024 – February 2025
Competition Overview
The Leeds Sustainability Case Competition (formerly Net Impact Case Competition) provides a forum for graduate students to solve real-world business problems by providing solutions with positive social, environmental, and financial impacts. Further, this international competition creates authentic opportunities for graduate students, companies, and sustainable business professionals to develop meaningful connections with one another.
Organizer: CESR - Leeds School of Business.
Case Summary
Perimas Technology, a privately held tech company, is rapidly expanding into the generative AI market based in Mountain View, California. To meet its 2030 AI business plan, the company anticipates a power demand of 2 terawatt-hours (TWh) annually. At the same time, Perimas remains committed to its science-based sustainability targets—reducing Scope 1 and 2 emissions by 50% by 2030 and reaching net-zero emissions by 2040. In addition to reducing operational emissions, the company seeks to innovate energy efficiency strategies using generative AI, and explore whether Scope 3 emissions should be addressed as part of its carbon strategy. Perimas aims to grow its U.S. AI market share from 0.55% to 2% by 2035, with a 25% annual growth rate.
See the full version of the case here.
Project Deliverables
Our team developed and pitched a comprehensive clean energy strategy for Perimas Technology, focused on enabling sustainable growth of its generative AI operations. Key components of our deliverables included:
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Energy Procurement Strategy: Recommended an optimal mix of power purchase agreements (PPAs), behind-the-meter (BtM) solar + storage, geothermal, and utility-scale renewable solutions
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Site Selection Analysis: Identified ideal locations for hyperscale and edge data centers based on grid carbon intensity, renewable potential, and market access
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Efficiency Measures: Proposed energy efficiency strategies aligned with data center expansion and SBTi-aligned emissions reduction targets
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Financial Modeling: Estimated power requirements to support Perimas’ projected AI market growth; calculated Opex/Capex, ROI for energy upgrades, and modeled long-term cost savings
My Role
I led technical and financial analyses, including power demand forecasting, market share projections, emissions alignment, and ROI calculations. I also introduced the concept of the “Three Energy Problem,” which structured our strategic framework and was featured in our Final Presentation.
