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The social economy is growing rapidly, and the power grid load demand is increasing. To maintain the stability of the power grid, it is crucial to achieve accurate and rapid power system stability assessment. In the actual operation of the power network, data loss is an unavoidable situation. However, most of the data‐driven models currently used assume that the input data is complete, which has obvious limitations in real‐world applications. This paper suggests an IVS‐GAN model to assess power system stability using incomplete phasor measurement unit measurement data with random loss. The proposed method combines the super‐resolution perception technology based on generative adversarial network (GAN) with a time‐series signal classification model. The generator adopts a 1D U‐Net network and uses convolutional layers to complete and recover missing data. The discriminator adopts a new gated recurrent unit–attention architecture proposed here to better extract voltage temporal variation features on key buses. The result of this paper is that the stability evaluation method outperforms other algorithms in high voltage data loss rates on the New England 10‐machine 39‐bus system. [ABSTRACT FROM AUTHOR]

A well-designed scheme is essential for assessment and protection of the stability of power system after an unanticipated event. This paper proposes a strategy for regulating three-phase faults and other events that endanger frequency or voltage stability of the system. The aim is to promptly identify such events utilizing supervised learning-based classification modules, and initiate suitable emergency control. The imbalances of active and reactive power after an event have been utilized to predict the stability of system. A new optimization-based formulation has been presented for estimation of reactive power imbalance. An event predicted as unstable is counteracted by prompt load shedding. Conventionally, load shedding is based on frequency or voltage information independently which reduces the effect of load shedding. This work proposes a new load shedding procedure considering both active and reactive power. The proposed scheme is tested on New England (NE) 39-bus system and Northern Regional Power Grid (NRPG) 246-bus system, and results of load shedding have been compared with two existing load shedding schemes. The results indicate the accuracy of classification modules in identifying faults and unstable events, and the proposed load shedding restores stability of the system with less amount of load shed and better voltage profile. [ABSTRACT FROM AUTHOR]

To solve the problem of manpower and time consumption caused by power flow state adjustment in a large-scale power grid, a power system operation state adjustment method considering the static stability constraint based on parallel deep reinforcement learning is proposed. By introducing the process of adjusting the power flow state that satisfies static stability, the Markov decision-making process of adjusting power flow is constructed. Then, based on the positioning of the adjustment target, the selection of actionable devices and the calculation of the amount of action, a power flow state adjustment strategy is developed. The adjustment process is accelerated through sensitivity, transfer ratio and load margin. Then, a parallel deep reinforcement learning model is established, and it maps actions to power flow adjustment to form a pair of generator actions and realises parallel adjustment of multi-sectional objectives. In addition, the reinforcement learning strategy and the deep learning network are improved to promote learning efficiency. Finally, the New England 39-bus standard system and actual power grid are used to verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

The transient stability margin is affected by different fault locations, fault clearing time and fault types that could be provided by protection information. This study presents an analytical on-line method of determining transient stability margin quantitatively using protection information for multi-generator system. First, the multi-machine system is equivalent to a one-machine infinity-bus system with the help of complementary cluster centre of inertia-relative motion. Second, the asymmetric fault models are built using positive rule, and the transient stability margin is then deduced by modelling the piecewise models of generator angles. Third, the practical transient stability margin assessment algorithm is then obtained. The sensitivity and affection mechanism of stability margin affected by fault factors are further derived, and the analytical stability margin is put forward to online access the transient stability margin after fault with the acquisition of the protection information. Finally, four- generator system, New England system and a real large power grid are used as test systems to verify the effectiveness and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Voltage source converter-based multi-terminal HVDC (VSC-MTDC) system has been considered for interconnecting asynchronous power grids for improved system operation efficiency and reliability. In this study, a frequency response control strategy is proposed for the VSC-MTDC systems that can enable operating reserves sharing among the interconnected asynchronous grids. The proposed control strategy consists of three frequency control components: MTDC primary frequency control, corrective frequency control, and MTDC secondary frequency control. The MTDC primary frequency control could keep the frequency of a disturbed power grid stable and avoid the frequency dropping into an unacceptable level when a sudden power imbalance event occurs. The corrective frequency control strives to guarantee the settled frequency can be within the predefined secure frequency range. The MTDC secondary frequency control provides a novel optimal allocation strategy for considering the participation of MTDC system for restoring system frequency back to the nominal frequency with the lowest cost. The simulation results, based on a modified IEEE New England 39-bus system modelled in PSCAD/EMTDC, show the effectiveness of the proposed frequency response control strategies. [ABSTRACT FROM AUTHOR]