Modern systems must trade off traditional performance goals with energy concerns, e.g., running faster lowers delays but increases power usage. However, while there are well-developed theories and models for discussing computation, communication, and memory demands of algorithms/systems, a theory for discussing the energy efficiency of an algorithm/system is only developing. In this talk, I will describe some recent work toward this goal, which focuses on dynamic capacity provisioning in data centers. Specifically, I will describe work that investigates (i) how much can be saved by dynamically "right-sizing" the data center through managing the number of active servers and (ii) how "geographical load balancing" can be used to make efficient use of renewable sources in Internet-scale systems. In both contexts I will present our new algorithms, which provide significantly improved performance guarantees when compared with the "standard" approaches using Receding Horizon Control. Additionally, if time allows, I will briefly discuss the our recent progress toward the implementation and evaluation of these algorithms in industry data centers.