Recently, there is a heightened level of awareness towards energy efficiency in high-performance data centers both to reduce environmental pollution and save cost. Such data centers consume massive amount of energy for processing huge computational requirements from users. These supercomputers demand a constant supply of electricity to be available 24/7 for both its core computing functions as well as cooling the data center. Previously, researchers had introduced various strategies for achieving energy efficiency. However, in order to achieve a truly effective energy management, factors that influence energy usages must also be taken into consideration. The failure to manage such factors leads to excessive energy consumption. In this work, we shall focus on factors relevant to running the operation of high-performance data centers. We reconstructed and analyzed such factors or attributes based on the universally accepted Reduce, Reuse and Recycle Concept (3R). We recategorized energy attributes of the existing Energy Efficient Data Center Frameworks (EEDCFs) to be aligned with 3R. Then, we developed energy-saving algorithms in response to the concept. Our framework was then measured according to the performance metrics namely power usage effectiveness (PUE), energy reuse effectiveness (ERE) and carbon usage effectiveness (CUE) against variability size of data center. The simulation results of our EEDCF showed that better energy saving is achieved in comparison to the existing EEDCFs. This signifies that the application of the 3R concept in energy consumption yielded a promising result as a platform for other researchers to explore more on energy renewal initiatives and embrace it for future application.