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An observer based adaptive detection methodology (ADM) is proposed for estimating frequency and its rate of change (RoCoF) of the voltage and/or current measurements acquired from an instrument transformer. With guaranteed convergence and stability, the proposed methodology effectively neutralizes the effect of the measurement distortions like harmonics, decaying DC components and outliers by adding its counter negative. It is robust to noise statistics, performs well while encountering step changes in amplitude/phase and is demonstrably superior to its precursors as established by test results. A benchmark IEEE NETS/NYPS 16 machine 68 bus power system has been used for performance evaluation of robust ADM against its precursors and scaled laboratory setup based on OP5600 multiprocessors was used for establishing its real-time applicability. [ABSTRACT FROM AUTHOR]

An adaptive decentralized control scheme is proposed for real-time control of oscillatory dynamics and overall stability improvement of an interconnected power system. A standard framework of continuous-time (CT) infinite-horizon optimal control paradigm is defined and an extended online actor-critic (AC) algorithm based on policy iteration is used for its solution. The AC structure uses neural networks (NNs) whose weights are updated adaptively. The proof for the convergence of the scheme guarantees the system stability. The unobservable internal states of the synchronous machine are estimated using a numerically stable, swift and relatively accurate decentralized dynamic state estimator (DDSE) based on spherical-radial cubature rule. Applicability of the developed scheme has been demonstrated on a benchmark power system (IEEE 2.2, 16 machine 68 bus system) model via nonlinear time-domain simulations. Multi-processor technology based scaled laboratory setup was used for controller performance validation in real-time. [ABSTRACT FROM AUTHOR]