Demand response control is one of the common means used for building peak demand limiting. Most of the existing demand response controls focused on single building's performance optimization, and thus may cause new undesirable peak demands at building group, imposing stress on the grid power balance and limiting the economic savings. A few latest studies have demonstrated the potential benefits of demand response coordination, but the proposed methods cannot be applied in large scales. The main reason is that, for demand response coordination of multiple buildings, associated computational load and coordination complexity, increasing exponentially with building number, are challenges to be solved. This study, therefore, proposes a hierarchical demand response control to optimize operations of a large scale of buildings for group-level peak demand reduction. The hierarchical control first considers the building group as a 'virtual' building and searches the optimal performance that can be achieved at building group using genetic algorithm. To realize such optimal performance, it then coordinates each single building's operation using non-linear programming. For validations, the proposed method has been applied on a case building group, and the study results show that the hierarchical control can overcome the challenges of excessive computational load and complexity. Moreover, in comparison with conventional independent control, it can achieve better performances in aspects of peak demand reduction and economic savings. This study provides a coordinated control for application in large scales, which can improve the effectiveness and efficiency in relieving the grid stress, and reduce the end-users' electricity bills.