16 citations · 17 across the 14 of their papers we have counts for
15 papers
Large-Scale Data Center Integration in Power Systems: Uncertainty and Multi-Scale Variation
Le Xie, Dongjoo Kim, Qian Zhang +2
Hyperscale artificial intelligence (AI) data centers are emerging as a structurally new class of electricity demand. Unlike conventional loads, they materialize as spatially concen…
Locational Marginal Pricing for Adaptive Robust Look-Ahead Dispatch with Casual Affine Recourse
Aidan Looney, Qian Zhang, Le Xie
This paper develops a marginal pricing mechanism for adaptive robust look-ahead economic dispatch (LAED) under net-load uncertainty. In current market practice, deterministic multi…
RestoreBench: Can AI Agents Restore Power Flow Convergence?
Riccardo Mansutti, Andrea Pomarico, Robert Jakob +3
Large Language Model (LLM) agents increasingly automate multi-step engineering workflows through tool use, interpretation of intermediate results, and iterative planning. Diagnosin…
Lost Opportunity Costs Under Ramp Stress: A Comparison of Ramp-Product Dispatch and Look-Ahead Economic Dispatch
Aidan Looney, Qian Zhang, Le Xie
This paper studies whether ramp-product settlement compensates generators that absorb intertemporal ramp scarcity as effectively as look-ahead economic dispatch. We evaluate this q…
PowerAgentBench-Dyn: A Benchmark for Agentic AI in Power System Dynamic Studies
Qian Zhang, Andrea Pomarico, Costas Mylonas +3
Large Language Model (LLM)-based agents are increasingly being used to automate multi-step engineering work flows by interacting with software tools, interpreting intermediate resu…
PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies
Costas Mylonas, Magda Foti, Andrea Pomarico +3
Power system benchmarks usually evaluate numerical solvers, prediction models, or sequential controllers. These benchmarks are necessary, but they do not directly test whether a La…
Modeling Coincident Peak Pricing in Electricity Markets: Challenges and Peak Shaving Effectiveness
Qian Zhang, Sadie Zhao, Lucy Diao +4
Coincident Peak (CP) pricing is widely used in U.S. electricity markets to allocate capacity and transmission costs. This paper develops a behavioral game-theoretic framework for C…
Comparative Assessment of Look-Ahead Economic Dispatch and Ramp Products for Grid Flexibility
Qian Zhang, Le Xie, Long Zhao +1
High renewable penetration increases the frequency and magnitude of net-load ramps, stressing real-time flexibility. Two commonly deployed remedies are look-ahead economic dispatch…
A Gradient-Based Capacity Accreditation Framework in Resource Adequacy: Formulation, Computation, and Practical Implications
Qian Zhang, Feng Zhao, Gord Stephen +2
Probabilistic resource adequacy assessment is a cornerstone of modern capacity accreditation. This paper develops a gradient-based framework, in which capacity accreditation is int…
Reformulating Energy Storage Capacity Accreditation Problem with Marginal Reliability Impact
Qian Zhang, Feng Zhao, Tongxin Zheng +1
To enhance the efficiency of capacity markets, many electricity markets in the U.S. are adopting or planning to implement marginal capacity accreditation reforms. This paper provid…
Accelerating Chance-constrained SCED via Scenario Compression
Qian Zhang, Le Xie
This paper studies some compression methods to accelerate the scenario-based chance-constrained security-constrained economic dispatch (SCED) problem. In particular, we show that b…
The Transmission Value of Energy Storage and Fundamental Limitations
Qian Zhang, P. R. Kumar, Le Xie
This study addresses the transmission value of energy storage in electric grids. The inherent connection between storage and transmission infrastructure is captured from a "cumulat…
The Role of Electric Grid Research in Addressing Climate Change
Le Xie, Subir Majumder, Tong Huang +4
Addressing the urgency of climate change necessitates a coordinated and inclusive effort from all relevant stakeholders. Critical to this effort is the modeling, analysis, control,…
Sample Complexity of Chance Constrained Optimization in Dynamic Environment
Apurv Shukla, Qian Zhang, Le Xie
We study the scenario approach for solving chance-constrained optimization in time-coupled dynamic environments. Scenario generation methods approximate the true feasible region fr…
Efficient Scenario Generation for Chance-constrained Economic Dispatch Considering Ambient Wind Conditions
Qian Zhang, Apurv Shukla, Le Xie
Scenario generation is an effective data-driven method for solving chance-constrained optimization while ensuring desired risk guarantees with a finite number of samples. Crucial c…