Distributed energy management algorithms eliminate the control center from the conventional energy management systems and calculate the optimal schedule for all devices through iterative coordination among neighbors. Most of the existing distributed approaches are developed under the assumption that all devices are secure and willing to achieve an optimal system performance together in a “collaborative” environment. However, unexpected faults and adversaries may emerge in the network and disrupt the convergence of those distributed approaches. In this paper, we extend the cooperative distributed energy scheduling (CoDES) algorithm to improve its resilience against data integrity attacks. Two types of data integrity attacks are considered in this paper - faulty attacks and random attacks. A distributed attack detection algorithm is developed to verify the state of neighboring devices without infringing their private information. A reputation-based mitigation algorithm is introduced to identify the compromised device and act accordingly to maintain the optimal energy scheduling result. The effectiveness of the proposed resilient distributed energy scheduling algorithm is evaluated in the Future Renewable Electric Energy Delivery and Management (FREEDM) microgrid system.