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The hybrid LCC/VSC cascaded HVDC (HC-HVDC) scheme, in which the LCC is adopted as rectifier, and one LCC in series with multiple paralleled VSC based MMCs is adopted as inverter, combines the advantages of both LCC and VSC-MMC technologies. Presently, a HC-HVDC project is planned to deliver the hydro power from Baihetan to Jiangsu in China. One of the major challenges is to suppress the DC overcurrent issue of VSC-MMCs especially under commutation failure condition of LCC at inverter side. Based on Baihetan-Jiangsu project under construction, the model of HC-HVDC system is developed in PSCAD/EMTDC. In the system, the rectifier employs a dual 12-pulse LCC, while the inverter adopts a hybrid scheme, i.e., one LCC converter in series with three paralleled VSC-MMC converters. This paper addresses the main cause and feature of the DC overcurrent, then proposes an overcurrent suppression control method for HC-HVDC system based on fuzzy clustering and identification approach. And the system transient performances with the proposed control approach are evaluated under AC fault conditions. The results show that the proposed approach can not only suppress the DC overcurrent following the commutation failure to a certain extent, but also improve the post-fault recovery performance of the overall system. [ABSTRACT FROM AUTHOR]

The uncertain nature of renewable energy resources (RERs) and fast demand response lead to recurring voltage violations in the power systems, which causes frequent transformer tap shifting and capacitor switching. Therefore, this paper resorts to the static var compensators (SVCs) to manage the bus voltages based on the multi-agent deep reinforcement learning (MA-DRL) algorithm. The proposed scheme includes several system agents and SVC agents to collaboratively adjust the injected reactive power to restrict the bus voltages within the normal range. All the agents are trained centrally and executed separately, which requires minimum communication cost. The IEEE 14-bus system, IEEE 300-bus system, and China 157-node urban power grid are used to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Faults on the alternating current (AC) transmission lines could cause commutation failures of nearby line-commutated converter-based high-voltage direct-current (LCC-HVDC) systems, which in turn, may challenge the fault detection of AC systems. To address this issue, this paper proposes a fast fault detection method based on instantaneous active power and fault variation component to alleviate the impacts of commutation failures and reactive power compensation while mitigating the dead zone problem. Upon that, an integral-based differential protection algorithm is presented to enhance reliability. Simulations are carried out on a real hybrid AC/DC system in North China with different fault locations and resistances to verify the effectiveness of the proposed method. Finally, we further validate the proposed method by leveraging on-site recorded fault data. [ABSTRACT FROM AUTHOR]

This paper proposes a dc voltage incipient sensor fault isolation method for single-phase three-level rectifier devices in high-speed railway electrical traction systems. Different incipient fault modes characterizing locations and incipient fault types are parameterized nonlinearly by unknown fault parameters. A new incipient fault isolation method is developed by combining sliding mode technique with nonlinear parameterization adaptive estimation technique. A bank of particular adaptive sliding mode estimators is proposed, which facilitates to derive new isolation residuals and adaptive threshold intervals. The isolability is studied, and the isolable sufficient condition is derived using new functions. For the practical electrical traction system in China Railway High-Speed 2, simulation and experiment based on TDCS-FIB (a software) are presented to verify the effectiveness and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]