Forced oscillation management in future power grids with high penetration of converter controlled-based resources

Forced oscillation (FO) events were detected in actual power systems, i.e., Nordic and Western America power systems. These events could result in the widespread blackout in the power systems. Accordingly, intensive researches in the FO detection, source identi cation and mit- igation are sought. In future power systems, conventional synchronous generators will be replaced by converter controlled-based generations (CCGs), i.e., wind and solar generations, and battery energy storage systems. Thus, the paradigm shift in power systems will lead to the inferior system strength and inertia scarcity. Therefore, problems of the FO detection, source identi cation and mitigation will emerge with new features of the CCGs. To deal with the aformentioned problems, the following contribu- tions are made in the thesis: i) a novel technique for detection of FO in a power system when the measured signals received through the com- munication channels are uncertain. Impacts of communication uncer- tainties on measured signals are theoretically investigated based on the mathematical models. Communication uncertainties are integrated in the remote signal measurements for monitoring and controlling of the FO. Theoretical investigation of the in uence of communication uncer- tainties such as variable latencies, packet disorders and packet losses on the FO analysis, and detection under several scenarios in a power system, is conducted. The development of data recovery technique to reconstruct the signal a ected by communication uncertainties is pro- posed with the establishment of the technique of continuous detection to improve the performance of the FO analysis and detection under vari- ous operations and communication uncertainties, ii) the new design and development of a controller termed as a forced oscillation damping con- troller (FODC) for damping FO considering uncertainty and periodic disturbances is proposed. An adaptive control algorithm is proposed to adjust the control parameters of FODC under various system oper- ations appropriately, uncertainties, and forced disturbances. Besides, a new control design for simultaneous inter-area and FO damping is pro- posed, iii) A uni ed FODC design method to deal with all oscillation caused by non-stationary FOs is proposed. Mathematical analyzes of the impacts of the non-stationary FO on electromechanical modes and sub/super synchronous modes considering various scenarios are con- ducted. The proposed solution consists of a continuous FO detection and robust-adaptive FO mitigation. A modi ed continuous detection is applied to monitor the non-stationary FO. Major stability indices such as damping, frequency, interaction, and robustness can be calculated without requiring exact system parameters, and v) A forced oscillation management framework incorporating the hierarchical neural network of distributed CCGs is proposed. Analyze and investigate the FO e ects in a low-inertia MG with distributed CCGs are conducted under various MG operating points, uncertainties, and FO conditions. The proposed method is able to properly manage big data produced from DCRs and suggest optimal solutions for FO detection, source identi cation, and mitigation in a low-inertia MG with DCRs. The simulation results show that the proposed methods in this thesis can accurate detect the FO under communication uncertainties. More- over, the proposed detection can di erentiate the FO from the elec- tromechanical oscillations. The proposed damping controller can sup- press both stationary and non-stationary FOs e ectively. Besides, the proposed FO management framework with the hierarchical neural net- work can detect and locate the FO source precisely, and suppress the FO in a low-inertia microgrid with CCGs automatically.