A reachable-set decomposition framework encodes remaining-horizon feasibility into per-period constraints for scalable real-time aggregation of multi-zone HVAC fleets via offline inner approximations and online parallel linear programs.
Leveraging two-stage adaptive robust optimization for power flexibility aggregation,
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A mean-field limit yields a convex, price-responsive surrogate for aggregated storage that is learned via gradient descent on historical data and converges with population size.
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Reachable-Set Decomposition for Real-Time Aggregation of Multi-Zone HVAC Fleets
A reachable-set decomposition framework encodes remaining-horizon feasibility into per-period constraints for scalable real-time aggregation of multi-zone HVAC fleets via offline inner approximations and online parallel linear programs.
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Mean-Field Learning for Storage Aggregation
A mean-field limit yields a convex, price-responsive surrogate for aggregated storage that is learned via gradient descent on historical data and converges with population size.