Research and Publications

My research asks how large energy users can become dependable resources for renewable-powered systems. I develop scalable, physically grounded models of how equipment investments and operations shape when and where energy is used, and I integrate them with power-system operations, macro-energy systems planning, and market design. My long-term goal is to build a demand flexibility economy in which firms can meet productive demand while reliably providing flexibility to power systems and earning predictable revenue in return.

Current Research

1. Modeling industrial flexibility for power-system interaction

Industrial demand flexibility is governed by material flows, task sequences, inventories, and discrete operating requirements. Detailed production-scheduling models capture these constraints but are often too computationally intensive for power-system applications, while simplified load models can misrepresent the flexibility that industrial users can actually provide.

I developed a modeling toolkit that makes physically grounded representations of industrial demand flexibility usable in energy-system planning and operations. The toolkit includes a continuous Resource Task Network for efficient production-process modeling, inverse optimization methods that infer plant parameters from smart-meter and electricity-price data, data-driven model reduction for system-scale studies, and real-time coordination methods for heterogeneous flexible resources.

Related publications

2. Providing seasonal grid flexibility through industrial overcapacity and storage

Demand flexibility depends not only on production scheduling but also on spare production capacity and inventory buffers. This led me to examine whether industrial overcapacity, usually viewed as an economic inefficiency, could instead become a long-duration flexibility resource for renewable-powered systems.

I developed a national-scale co-optimization framework linking industrial operations with power-system expansion. Applied to China's aluminum sector, the framework showed that spare production capacity and product inventories can shift production, and therefore electricity use, across seasons. Across the investigated scenarios, this flexibility reduced annual electricity-system costs by CNY 23-32 billion, equivalent to 11-15% of the aluminum smelting industry's product value.

Related publications

3. Valuing and procuring dependable demand flexibility

Demand flexibility can reduce generation, storage, and grid investment, but firms bear capital, inventory, and operating costs when they provide it. Without procurement mechanisms that recognize these costs and reward reliable delivery, firms have little incentive to modify their assets or operations for power-system needs.

I developed a life-cycle cost framework that compares industrial and data-center load shifting with energy storage across timescales while accounting for costs borne by flexibility providers. I am extending this work by linking power-system planning models that quantify avoided infrastructure costs with firm-level investment models. This framework will support comparisons among utility procurement, bilateral contracts, and organized markets, including how availability payments, performance payments, contract duration, and verification requirements affect investment and participation.

Related publications

Complete Publication Record

See my Google Scholar profile or download my CV for the complete publication list.