Hierarchical distributed multi-energy demand response for coordinated operation of building clusters

This paper proposes a distributed multi-energy demand response (DR) methodology for the optimal coordinated operation of smart building clusters based on a hierarchical building-aggregator interaction framework. In the proposed hierarchical framework, the aggregator acts as a digital representation of building entities to offer the multi-energy load prediction of buildings using a capsule network (CapsNet) based multi-energy demand prediction model, while these buildings leverage the load flexibility and multi-energy complementarity to implement the optimal DR for reducing individual costs. Then, a fully distributed multi-energy DR approach based on the exchange alternating direction method of multipliers (ADMM), which requires only limited information to be exchanged between the aggregator and buildings, is developed to iteratively achieve the optimal multi-energy coordination of buildings. Moreover, the proposed model can be dynamically corrected with real-time load data and weather information, and the distributed multi-energy DR approach is correspondingly optimized with rolling horizon procedures to reduce the impact of prediction uncertainties. Finally, the performance of the proposed methodology is benchmarked and validated on different scales of smart buildings, and comparative results demonstrated its superiority in solving the optimal synergistic operation problem of smart buildings.