OPF-Based Optimal Power System Network Restoration Considering Frequency Dynamics

Due to recent blackout and system split incidents in power grids worldwide, as well as increased system complexity in view of the energy transition, there has been increasing interest in re-evaluating existing Power System Restoration (PSR) plans. In restoration scenarios, due to low island inertia, it is necessary to ensure not only the static, but also the dynamic stability of the system. In this paper, we pose and solve a formulation of the optimal PSR problem including frequency dynamics. We validate the switching constraints for global optimality within a static version of the formulation using a brute-force tree search method. We apply the dynamic problem formulation to the IEEE 9-Bus model, and show that the optimal switching sequence using the static formulation would violate dynamic constraints, illustrating the importance of dynamic considerations in PSR planning.

Identification of Power System Dynamic Model Parameters using the Fisher Information Matrix

The expected decrease in system inertia and frequency stability motivates the development and maintenance of dynamic system models by Transmission System Operators. However, some dynamic model parameters can be unavailable due to market unbundling, or inaccurate due to aging infrastructure, non-documented tuning of controllers, or other factors. In this paper, we propose the use of a numerical approximation of the Fisher Information Matrix (nFIM) for efficient inference of dynamic model parameters. Thanks to the proposed numerical implementation, the method is scalable to Electromagnetic Transient (EMT) models, which can quickly become computationally complex even for small study systems. Case studies show that the nFIM is coherent with parameter variances of single- and multi-parameter least-squares estimators when applied to an IEEE 9-bus dynamic model with artificial measurements.

A Synchrophasor Estimator Characterized by Attenuated Self-Interference and Robustness Against DC Offsets: the DCSOGI Interpolated DFT

The second-order generalized integrator (SOGI), which can be used to attenuate the self-interference of the fundamental tone, is unable to reject DC offsets on the input signal. Consequently, the performance of any SOGI based synchrophasor estimation (SE) technique might be compromised in the presence of such DC components. The current work presents a SE algorithm which adopts and enhanced SOGI formulation, robust against DC, combined with a three-point IpDFT and a Hanning window. Two alternative formulations relying respectively on the use of two and three nominal fundamental period observation windows are proposed and assessed for simultaneous compliance with both phasor measurement unit (PMU) P and M performance classes. This is done by means of a simulated environment where all the operating conditions defined by the IEC/IEEE Std. 60255-118-1-2018 are evaluated simultaneously combined with a $10\%$ static DC and under two different noise levels. Furthermore, both formulations adopt a dedicated mechanism for the detection and correction of low amplitude $2^{nd}$ harmonic tones to ensure their compliance with the standard can be maintained in the presence of such disturbances even under off-nominal frequency conditions. Finally the resilience of both methods against multiple simultaneous harmonic interferences is also analyzed.

Functional Basis Analysis for the Characterization of Power System Signal Dynamics: Formulation, Implementation and Validation

With the integration of distributed energy resources and the trend towards low-inertia power grids, the frequency and severity of grid dynamics is expected to increase. Conventional phasor-based signal processing methods are proving to be insufficient in the analysis of non-stationary AC voltage and current waveforms, while the computational complexity of many dynamic signal analysis techniques hinders their deployment in operational embedded systems. This paper presents the Functional Basis Analysis (FBA), a signal processing tool capable of capturing the full broadband nature of signal dynamics in power grids while maintaining a streamlined design for real-time monitoring applications. Relying on the Hilbert transform and optimization techniques, the FBA can be user-engineered to identify and characterize combinations of several of the most common signal dynamics in power grids, including amplitude/phase modulations, frequency ramps and steps. This paper describes the theoretical basis and design of the FBA as well as the deployment of the algorithm in embedded hardware systems, with adaptations made to consider latency requirements, finite memory capacity, and fixed-point precision arithmetic. For validation, a PMU calibrator is used to evaluate and compare the algorithm's performance to state-of-the-art static and dynamic phasor methods. The test outcomes demonstrate the FBA method's suitability for implementation in embedded systems to improve grid situational awareness during severe grid events.

Computationally-Efficient Synchrophasor Estimation: Delayed in-quadrature Interpolated DFT

The paper proposes a synchropahsor estimation (SE) algorithm that leverages the use of a delayed in-quadrature complex signal to mitigate the self-interference of the fundamental tone. The estimator, which uses a three-point IpDFT combined with a three-cycle Hanning window, incorporates a new detection mechanism to iteratively estimate and remove the effects caused by interfering tones within the out-of-band interference (OOBI) range. The main feature of the method is its ability to detect interfering tones with an amplitude lower than that adopted by the IEC/IEEE Std. 60255-118, this detection being notably challenging. Furthermore, it simultaneously satisfies all the accuracy requirements for the P and M phasor measurement unit (PMU) performance classes, while offering a reduction in the total computational cost compared to other state-of-the-art techniques. Despite an increase in total memory requirements, a preliminary analysis reveals its suitability for implementation on embedded devices.