In this dissertation, approaches for measurement based real-time wide-area damping controllers (WADC), are studied for renewable energy integrated power grid. For this, first, a model-free algorithm for multi-input-multi-output (MIMO) transfer function identification of the power system is presented. The MIMO identification is based on actual measurements which can monitor changes in the grid as opposed to conventional methods that are based on the small-signal analysis. An optimal control loop for WADC is estimated using the identified MIMO system. The WADC design is based on the discrete linear quadratic regulator (DLQR) and Kalman filtering for real-time damping of inter-area oscillations. This methodology is then modified by incorporating an online coherency properly characterizes real-time changes. The WADC architecture is then decentralized using the Alternating Direction Method of Multipliers (ADMM). Further, for large-scale power system implementation, Frequency-Dependent Network Equivalent (FDNE) are designed that can aggregate the power grid based on the study area and external area classified utilizing the grid property of special complexity. The FDNE is used for two applications a) Pitch Control of Wind Farms and b) Reducing the grid model to implement the proposed WADC. The architecture is tested and validated on a RTDS/RSCAD and MATLAB real-time co-simulation platform using two-area and IEEE 39 bus power system models.