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Summary: Subsequent commutation failure (CF) elimination in line‐commutated‐converter–based high‐voltage direct current (LCC‐HVDC) is an essential issue of AC/DC hybrid power systems. Since methods based on improving HVDC control systems or advancing the firing angle have inherent limitations, adjustment of the DC current order is regarded as an effective emergency control strategy for HVDC that has been put into operation. However, existing methods sometimes result in failed CF elimination due to improper control timing of DC current. In order to determine proper control timing, novel voltage indexes are put forward in this article to identify stability or instability of the hybrid system. Then, the DC current order is adjusted in real time to eliminate subsequent CF according to the evaluation results given by the proposed voltage indexes. The control strategy is simulated in the PSCAD/EMTDC platform as well as actual power system, and the simulation results compared with those of existing schemes verify the effectiveness and advancement of the proposed strategy on subsequent CF elimination. [ABSTRACT FROM AUTHOR]

This paper briefly introduces the existing methods for voltage sag source location and theoretically analyzes some reasons why high accuracy cannot be achieved by using these methods. Based on the redefined voltage sag source location 'reference direction' and the analysis of voltage sag source's influences in power network, it is pointed out that observing from disturbance source point to both sides of monitoring services, any power network can be equivalent to 2 active single-port networks and the networks can be equally replaced by 'Thevenin's equivalent circuit.' By judging the sign of the internal resistance in Thevenin' s equivalent circuit, the origin of voltage sag disturbance can be easily identified. The calculation of internal transient resistance is given based on the application of space vector theory. This method can locate voltage sag source with an accuracy of 100% verified by simulation experiments. It is a very practical method that is not only applicable in radial and nonradial power systems but also in networks of neutral grounded effectively or ineffectively. [ABSTRACT FROM AUTHOR]

This paper presents a simplified voltage control of paralleling doubly fed induction generators (DFIGs) connected to the grid by using static Var compensator (SVC). The DFIG converters are based on a voltage source converter in the grid side converter (GSC) and current source converter in the rotor side converter (RSC). The GSC is employed to work like static synchronous compensator (STATCOM) to provide precise control to maintain the DC link voltage under control. The RSC is oriented to control real and reactive powers of the DFIG. Instead of adding two SVCs in every DFIG bus it connects only one SVC in the point of common coupling of the generators to enhance the voltage stability at a steady state and dynamic operation by decreasing the reactive power hence to increase the voltage amplitude. The comprehensive simulations are carried out using PSCAD/EMTDC program. The results show that the SVC has improved voltage stability and promote the system transient response by compensating reactive power. Furthermore, this study has presented the possibility of using one SVC with low capacity based on the SVC characteristics adjusted only by choosing a suitable transformer rating. Moreover, the system model simulation was tested at steady state and dynamic mode during constant and random wind speeds. Using one SVC with low capacity leads to decrease power dissipation, and this directly reduced the power cost. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Transient frequency prediction helps formulate and take emergency control measures in a timely way, which is of great significance to the security and stability of a power system. Conventional frequency prediction methods encounter challenges when taking both speed and accuracy into account. Machine–learning‐based prediction methods cannot readily achieve satisfactory prediction accuracy based on historical samples of transient faults; only by updating the prediction model online can these methods accommodate a transient fault, which may occur at any time. Aiming at the online update of the prediction model, the concept of data inheritance is presented and applied to the process of model updating. Based on this update method, a transient frequency prediction method considering model inheritance is proposed. In this prediction method, the historical transient fault samples of the power system are used to train the initial prediction model; in this way, the prediction performance can be quickly improved according to the newly incremented transient fault samples by inheriting the historical prediction model. Validations on the New England 39‐bus and NPCC 140‐bus systems demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]