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Hybrid high voltage direct current systems utilized for bulk-power transmission have recently attracted more attention. The overhead lines (OHLs) are mainly used for the implementation of such systems due to their outstanding economic advantages. However, OHLs are vulnerable to temporary faults, jeopardizing the safe and reliable operation of the network. The resiliency to the line faults is of considerable significance to the power transmission. This paper proposes a fault property identification strategy based on the Pearson correlation coefficient for the LCC-MMC hybrid HVDC system which can differentiate temporary and permanent faults. To achieve this, a voltage signal is injected into the faulty line by decreasing the firing angles of the LCC-based rectifier. Based on the established OHLs model and the injected signal, an estimated backward travelling wave can be accurately calculated. The fault property is identified by comparing the wave difference of the real backward travelling wave and the estimated backward travelling wave. The proposed strategy has a high accuracy since all influencing factors including the fault resistance, fault distance, and line parameters have been taken into account. Finally, to verify the efficacy of the proposed algorithm, several simulations have been performed using PSCAD/EMTDC. The simulation results show that the proposed algorithm can effectively distinguish the fault property. [ABSTRACT FROM AUTHOR]

DC short-circuit current calculation is necessary to design and protect modular multilevel converter-based (MMC-based) multiterminal dc (MTDC) grids. In this article, a general and analytical short-circuit current calculation method is proposed for bipolar MTDC grids. For pole-to-pole (P2P) faults, the superposed fault equivalent network of the MTDC grid is first developed in the frequency-domain. Then, a decoupling method based on the network inductance ratio is proposed, which simplifies the high-order network into the superposition of several independent two-order RLC circuits. As a result, the short-circuit current can be expressed as the sum of the currents of these RLC circuits. For pole-to-ground (P2G) faults, the phase-domain dc line impedance considering the coupling effects is determined based on its modal-domain parameters, so that the P2G fault current can be calculated using the method of the P2P fault. The proposed method’s effectiveness is verified through simulations and experiments, and the calculation error is classified and analyzed. Compared with the existing methods, the proposed method is more accessible, more accurate, and available for hand-solution. [ABSTRACT FROM AUTHOR]

This paper presents data-driven approaches to improve the active power output of wind turbines based on estimating their health condition. The main procedure includes estimations of fault degree and health condition level, and optimal power dispatch control. The proposed method can adjust the active power output of individual turbines according to their health condition and can thus optimize the total energy output of a wind farm. In the paper, extreme learning machine algorithm and Bonferroni interval are applied to estimate fault degree, while an analytic hierarchy process is used to estimate the health condition level. A scheme for power dispatch control is formulated based on the estimated health condition. Models have been identified from supervisory control and data acquisition data acquired from an operational wind farm, which contains temperature data of gearbox bearing and generator winding. The results show that the proposed method can maximize the operation efficiency of the wind farm while significantly reducing the fatigue loading on the faulty wind turbines. [ABSTRACT FROM AUTHOR]