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This paper addresses the problem of run-time management of a service centre energy efficiency by using a context aware self-adapting algorithm. The algorithm considers the service centre current context situation and predefined Green/Key Performance Indicators (GPI/KPI) to adapt and optimize the service centre energy consumption to the incoming workload. The service centre energy performance context situation is obtained by collecting service centre current context data related to the business applications scheduled to run on service centre resources, service centre IT computing resources and the service centre facilities. A reinforcement learning approach is used to decide the best sequence of actions to be executed to bring the service centre resources as close as possible to a GPI and KPI compliant state while minimizing the energy consumption.