Demand response (DR) control is one of the common means used for building peak demand limiting. Most of the existing DR controls focused on performance optimization of single building, 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 DR coordination, but the proposed methods cannot be applied in large scales. The main reason is that, for DR coordination of multiple buildings, associated computational load and coordination complexity, increasing exponentially with building number, are challenges to be solved. This chapter, therefore, proposes a hierarchical DR control to optimize the building operations in large scales for building group 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 (GA). To realize the GA-based optimal performance, it then coordinates each single building’s operation using non-linear programming (NLP). For validations, the proposed method has been applied on a case building group, and the study results show that the hierarchical DR control can overcome the challenges of excessive computational load and complexity. Moreover, in comparison with conventional independent DR control, it can achieve better performances in aspects of peak demand reduction and economic savings. This chapter provides a coordinated DR control method for application in large scales, which can improve the effectiveness and efficiency in relieving the grid stress, and reduce the electricity bills of the end-users. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.