Identifying the Sources and Parameters of Disturbances in Power Systems
Creators: name: Mansouri Habibabadi, Mohammad
Publisher: name: Schulich School of Engineering
Year: 2022
Subjects: subject: Power system dynamic
subject: Electromechanical oscillations
subject: Harmonics
subject: Forced Oscillations
subject: SOGI
subject: Internal Model Priniciple
subject: Blind identification
subject: Engineering--Electronics and Electrical

description: The high penetration of renewable energy in power systems makes power systems dynamically more complicated; hence, a power system faces frequent disturbances, including electromechanical oscillations, harmonics and subharmonics, and forced oscillations. Furthermore, because a power system is dynamically complicated, the classic methods that mainly rely on the system’s dynamic model cannot work as it is hard to have the details of the power systems dynamic or is impossible. Therefore, measurement-based methods, which do not need the system dynamic, have received significant attention in recent years. This dissertation offers measurement-based methods to identify and mitigate three disturbances, including electromechanical oscillations, harmonics and subharmonics, and forced oscillations. The contribution of this research can be divided into four parts.The first contribution proposes a measurement-based strategy to estimate the parameters of the multi-mode electromechanical oscillations. This strategy employs the cascade structure of Damped-SOGI to estimate the parameters of electromechanical oscillations. The advantages of the proposed method are the capability of online implementation, robustness against noise, no need for dynamics of the system, no need to pre-filtering and pre-processing, and simplicity.The second contribution of this thesis is an algorithm to mitigate electromechanical oscillations. In this algorithm, the dynamic of electromechanical oscillations is extracted by the Damped-SOGI; afterward, this dynamic is placed in the control loop. Thus, the electromechanical oscillations are rejected from the power systems output based on the Internal Model Principle (IMP). Computer simulation and experimental results confirm the effectiveness of the proposed method.An algorithm to identify the source of harmonics and subharmonics is proposed as the third contribution of this dissertation. In this algorithm, the N4SID, an identification method, extracts the power system’s dynamics and inputs. Afterward, the source of the subharmonic is identified by studying the correlations between various extracted inputs. Simplicity and robustness against noise are of the advantages of the proposed algorithm.Locating the source of forced oscillations is tackled by subspace identification in the fourth contribution of this thesis. In this algorithm, the dynamic model of the power system is identified by subspace identification. Using the identified model, the dynamic responses of the forced oscillation are extracted in each PMU location. Finally, the source of forced oscillation is deter- mined by studying the magnitude and phase or the correlations of extracted forced oscillations. The capability to distinguish between forced oscillations and electromechanical oscillations is of the advantages of the proposed algorithm.