We consider a novel multi-server queueing system that is potentially useful for optimizing real-world systems, in which the objectives of high performance and low power consumption are conflicting. The queueing model is formulated and investigated under the assumption that an arrival flow is defined by a batch Markovian arrival process and random values characterizing customer processing have the phase-type distribution. If the service time of some customer by a server exceeds a certain random bound, this server receives help from a so-called backup server from a finite pool of backup servers. The behavior of the system is described by a quite complicated multi-dimensional continuous-time Markov chain that is successfully analyzed in this paper. Examples of the potential use of the obtained results in managerial decisions are presented. © 2017 Elsevier Inc.