Energy consumption is becoming a growing concern in data centers. Many energy-conservation techniques have been proposed to address this problem. However, an integrated method is still needed to evaluate energy efficiency of storage systems and various power conservation techniques. Extensive measurements of different workloads on storage systems are often very timeconsuming and require expensive equipments. We have analyzed changing characteristics such as power and performance of stand-alone disks and RAID arrays, and then defined MIND as a black box power model for RAID arrays. MIND is devised to quantitatively measure the power consumption of redundant disk arrays running different workloads in a variety of execution modes. In MIND, we define five modes (idle, standby, and several types of access) and four actions, to precisely characterize power states and changes of RAID arrays. In addition, we develop corresponding metrics for each mode and action, and then integrate the model and a measurement algorithm into a popular trace tool – blktrace. With these features, we are able to run different 10 traces on large-scale storage systems with power conservation techniques. Accurate energy consumption and performance statistics are then collected to evaluate energy efficiency of storage system designs and power conservation techniques. Our experiments running both synthetic and realworld workloads on enterprise RAID arrays show that MIND can estimate power consumptions of disk arrays with an error rate less than 2%.