Abstract:

Exogenous disturbances such as occupancy and weather strongly affect the per- formance of grid-interactive buildings, making accurate probabilistic forecasting essential for robust control. We propose a new MQF2-TFT architecture that captures both temporal and cross-variable dependencies for multi-horizon disturbance forecasting. To integrate forecasts into stochastic MPC, we develop a quantile- based sample method that enforces chance constraints despite non-Gaussianity. Experiments with real office building data demonstrates improved key performance indicators over baselines.