The 21st-century electric power grid is transitioning from a centralized structure designed for bulk-power transfer to a distributed paradigm that integrates the variable renewable energy (VRE) resources spatially distributed across the grid. This work proposes algorithmic solutions for distributed economic dispatch based on Subgradient method and Alternating Direction Method of Multipliers (ADMM), both designed to be agnostic with any initialization vector. The proposed distributed online solutions leverage a dynamic average consensus algorithm to track the time-variant linearly coupled constraint that allows an abrupt change in power demand of the network because of the high penetration of VRE resources. The problems are modeled as discrete dynamic systems to investigate the stability and convergence of the algorithm. The update procedures are designed such that the iterates converge to the optimal solution of the original optimization problem, steered by the gain parameter corresponding to the second largest eigenvalue of the system matrix
