Reachable-Set Decomposition for Real-Time Aggregation of Multi-Zone HVAC Fleets

TL;DR

This paper introduces a decomposition framework for real-time aggregation of multi-zone HVAC fleets, enabling scalable, feasible, and efficient flexibility characterization and disaggregation.

Contribution

It develops a reachable-set decomposition method with offline and online stages, improving computational tractability and feasibility guarantees for HVAC fleet management.

Findings

Effective aggregate flexibility characterization demonstrated in case studies.

Tractable computation via parallel linear programs and Minkowski summation.

Guarantees of feasibility over the remaining horizon for any reported flexibility.

Abstract

Aggregating building heating, ventilation, and air-conditioning (HVAC) fleets provides substantial real-time flexibility to power system operations. However, real-time aggregation of multi-zone HVAC fleets faces two key challenges: (i) strong coupling across zones and time makes flexibility characterization high-dimensional and computationally demanding, and (ii) the sequential revelation of temperature states and exogenous conditions requires that decisions made at each period preserve feasibility over the remaining horizon using only currently realized information. To address these challenges, this paper proposes a reachable-set decomposition framework comprising an offline decomposition stage and a real-time policy. In the offline stage, backward reachable sets are formulated to encode remaining-horizon feasibility into per-period state constraints, so that any state within the current reachable set is guaranteed to sustain feasible operation over the entire remaining horizon. A tailored inner approximation is then developed for tractable calculation in multi-zone-coupled HVAC settings. In the real-time stage, aggregate flexibility is computed efficiently via building-level parallel linear programs followed by closed-form Minkowski summation of power intervals, and any regulation signal within the reported flexibility interval admits a recursively feasible disaggregation. Case studies demonstrate the effectiveness of the proposed framework in aggregate flexibility characterization, disaggregation feasibility, and scalable computation.