PowerCodeBench and a boundary-aware intervention raise LLM accuracy on power-system code generation by 32-56 points across ten open-weight models and four commercial APIs on a 2,000-task benchmark.
Hybrid symbolic-numeric framework for power system modeling and analysis.IEEE Transactions on Power Systems, 36(2):1373–1384, 2021
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A hybrid energy storage system with residual differentiable predictive control reduces AI datacenter-induced grid frequency deviations by over 80 percent in NPCC 140-bus simulations.
QADR decomposes n-qubit VQCs into local sub-circuits to reduce memory from O(2^n) to O(n * 2^{2d+1}) and mitigate barren plateaus, scaling to 2000 features on MNIST and wind turbine diagnostics while matching classical models.
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Source Side Mitigation of AI Datacenter Power Fluctuations with a Hybrid Energy Storage System and Residual Differentiable Predictive Control
A hybrid energy storage system with residual differentiable predictive control reduces AI datacenter-induced grid frequency deviations by over 80 percent in NPCC 140-bus simulations.