Distributed oscillation damping estimation to large scale power systems: A multi-area online empirical approach

- The generalization of the Prony and Fourier based methods to muti-area analysis.
- An analytical framework to extract multi-area matching patterns modes is presented.
- A sliding data window frame is included to develop an optimal online algorithm.
- Multiple EOFs analysis from coherent signal blocks is introduced using WAMS.
- A new online algorithm to the distributed damping estimation is proposed.

Online extraction and characterization algorithms to the distributed damping factor that can accurately monitoring the transient response in large interconnected power systems has attracted much attention, principally to maximize the multi-area functions in energy control centers. In this paper we present an online estimation algorithm to the distributed damping factor of inter-area electromechanical oscillations in power systems. The method is based on a statistical analysis of multi-area matching patterns (MPs) modes from spatially coupled empirical coefficients, and derived with a network partitioning method by coherent signal blocks into data clusters from the phase domain. This provides a distributed global picture on the modal behavior, which is derived using synchronized-time multi-area signals simultaneously recording from wide-area monitoring schemes (WAMS). For purposes as our multi-area online approach, a sliding data window frame for estimating the distributed damping factor of low-frequency electromechanical oscillations based on Prony and Fourier methods with multiple empirical orthogonal functions (EOFs) analysis is presented. In order to demonstrate the usefulness and adaptivity to obtain an online damping factor estimation and global picture of inter-area electromechanical modes from dynamic oscillations in distributed power systems, the proposed algorithm is applied in detail to the 16 machine-68 bus New England test system.