The TSO of a power system is mainly responsible for ensuring the stability of the grid. Through continuous monitoring and control of the power system, the TSO maintains stability through emergency actions. Until now, the conventional Static State Estimation has been the Energy Ma
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The TSO of a power system is mainly responsible for ensuring the stability of the grid. Through continuous monitoring and control of the power system, the TSO maintains stability through emergency actions. Until now, the conventional Static State Estimation has been the Energy Management System (EMS) tool for estimating and monitoring the grid state - bus voltages, currents, and powers. However, energy transition, which involves the decommissioning of conventional generation and their replacement by renewables, leads to a more dynamic grid. In such a case, the information provided by the static state estimator is insufficient. This has, hence, led to the development of the Dynamic State Estimator (DSE), to provide insight into the dynamic properties of a power system, such as rotor angle and rotor speed. The DSE typically uses a Wide-Area Monitoring (WAMS) architecture consisting of Phasor Measurement Units (PMU), to dynamically estimate the internal states of the generators under observation. Hence, the DSE provides improved situational awareness to the TSO. However, the existing literature do not elaborate on how their proposed DSE can be implemented in an online fashion to estimate the dynamic states in near real-time. Such an online implementation is of utmost importance as it showcases how a TSO can deploy the DSE in a real world scenario. Hence, this thesis proposes an online DSE algorithm that performs batch-wise estimation of dynamic states in a near real-time setting. By collecting measurements in batches and introducing the pre-processing steps necessary for these PMU measurements, the algorithm forms the premise for the real-world application of DSE. This algorithm is validated using a cyber-physical testbed comprising a Real Time Digital Simulator and a Synchrophasor Application Development Framework. Additionally, its performance is evaluated and a sensitivity study is conducted to find deterministic relationships between the input error introduced and the estimation error. Finally, future improvements are proposed to make the implementation more suitable to real-world application.