Decentralised peak energy demand minimisation in networks of buildings

Abstract

Simultaneous peaks in the energy demand from networks of buildings can decrease system stability and increase operational costs. However, reducing these peaks can require complicated centralised control schemes. Here, taking inspiration from biological systems, we investigate a decentralised, building-to-building load coordination schema that requires very little information and no human intervention. Using agent-based modelling, we investigate both the optimal system size and robustness of the results to changes in the system parameters. It is found that substantial reductions are readily achieved through coordination between a small number of buildings, analogous to models of coordination between flocks of birds. Strikingly, the schema significantly outperforms existing techniques and is robust to varying network topology and the inclusion of large time-constrained thermal loads. These results imply that significant reductions in network peaks are achievable through simple low-cost controllers implemented at the building level; particularly important for developing countries with fragile networks.