Haochi’s research interests include the energy-water nexus, climate adaptation, macro energy systems, and efficient data-driven energy system operation. His research leverages energy system modeling, power system economics, convex optimization, and machine learning to support the optimization and analysis of complex systems.
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Overview
Most pathways for decarbonizing the electricity sector by 2050 include substantial increases in intermittent renewable generation paired with several TWh of grid-scale energy storage. Grid scale storage includes the ability to shift or schedule large amounts of power over time and can be deployed via a diverse range of technologies, like batteries or pumped hydropower. This project aims to understand the degree to which we can use existing infrastructure as virtual storage, by scheduling the operations and consequently the power consumption of electrified industrial processes (e.g., water treatment plants, chemical manufacturing, data centers, etc.). Our group develops methods rooted in numerical optimization to design, operate, and evaluate energy flexibility strategies across a range of industrial sectors and geographic regions. By modeling these processes from the ground up, we aim to understand the cost and feasibility requirements to unlock more flexibility from existing infrastructure and strategies to design and deploy flexibility more effectively for next generation infrastructure.
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Overview
Data centers are among the fastest-growing electricity consumers in the U.S. and also require substantial cooling water, imposing significant economic and environmental impacts on water and energy systems. Because they can respond to changes in electricity prices, emissions, water availability, and utility incentive programs, data centers are strong candidates for flexible, dynamic operation—yet operators and policymakers lack the datasets needed to decide where to site facilities and how to operate them. This project develops a national, geospatial dataset spanning retail electricity and water costs, Scope 2 emissions, grid reliability, water supply sustainability risk, time-of-use tariffs, and demand response programs to inform data center siting and flexible operation. Preliminary analysis across the eight most common U.S. data center regions quantifies the tradeoffs between candidate locations—for example, low electricity costs in Phoenix are accompanied by high Scope 2 emissions and the most at-risk water supply—informing site-specific permitting, utility incentive design, and operational decisions.
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Overview
The U.S. power system is facing unprecedented load growth driven largely by data centers for AI and large-scale computing, carrying significant greenhouse gas and water-consumption footprints that depend heavily on where facilities are sited. Existing analyses predominantly rely on static, short-run emissions assessments that fail to capture the bi-directional interaction between large new loads and the grid's long-term evolution. This project couples data center load-growth scenarios—spanning energy efficiency, flexible operation, and siting—with a power grid capacity expansion model to determine how siting and operating decisions shape, and are shaped by, future investment in generation, storage, and transmission. By comparing uniformly distributed load, clustering in today's major markets, and DOE-recommended sites, we quantify the system-wide cost, emissions, and water-consumption implications of different deployment pathways, helping policymakers and utilities mitigate the economic and environmental costs of AI growth while enabling data centers to come online in reasonable timeframes.
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Overview
California’s industrial, agriculture, and water sectors account for approximately 25% of the state’s electricity consumption and present a substantial opportunity for load flexible technologies to optimize energy use and reduce operational costs. The Industrial Agriculture and Water (IAW) FlexHub’s goal is to deploy demonstrations with accessible, quantifiable, and transferable results for energy transformation everywhere. WE3 Lab is working with IAWHub to externalize a set of digital tools that enable water utilities and similar industrial facilities to value, assess, and deploy energy demand flexibility.
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