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Decentralized High - Reliability Energy Management Regime for Smart Building

This paper focuses on developing a fully decentralized energy management regime (EMR) for smart buildings to respond to the utility grid for peak-load shifting. The proposed EMR is constructed based on the robust tube model predictive control theory, which includes two stages: day-ahead scheduling and real-time operation. At the day-ahead scheduling stage, a smart building flexible resources robust scheduling problem is considered to ensure the reliability of power supply; at the real-time operation stage, a rolling correction based operational strategy is studied to minimize the deviation of actual and day-ahead scheduling. A multi-stage energy management model based on min-max robust optimization technology is constructed to provide quantitative decision support for the energy management of smart buildings. Moreover, the constructed mathematical model is solved by a fully decentralized algorithm based on consensus theory and the alternating direction method of multipliers for privacy security and “plug-and-play” purposes. Simulation and experimental results demonstrate that the effectiveness and computational efficiency of the proposed model and solving algorithm even in the presence of high system uncertainties.