Nowadays, data are generated and accessed from all over the world. Applications and companies store these data on geo-distributed cloud providers that have to be profitable while reducing their environmental impact. As Cloud providers aim to satisfy their service level objectives in terms of availability and response time, they often rely on data replication. In this paper, we propose a dynamic data replication strategy (DE2ARS) that adapts the number of replicas according to the workload and addresses energy consumption and expenditure issues. It follows an initial placement and is triggered by a Control Chart. We first compare different parameter choices in order to provide better analysis for the proposed strategy. We compare DE2ARS with strategies from the literature. Results highlight the fact that DE2ARS reaches its goal to reduce both energy consumption and expenditure while having good performance in a strong workload context.