With the interconnection between large power grids, the issue of security and stability has become increasingly prominent. At present, data-driven power system adaptive transient stability assessment methods have achieved excellent performances by balancing speed and accuracy, but the complicated construction and parameters are difficult to obtain. This paper proposes a stacked-GRU (Gated Recurrent Unit)-based transient stability intelligent assessment method, which builds a stacked-GRU model based on time-dependent parameter sharing and spatial stacking. By using the time series data after power system failure, the offline training is performed to obtain the optimal parameters of stacked-GRU. When the application is online, it is assessed by framework of confidence. Basing on New England power system, the performance of proposed adaptive transient stability assessment method is investigated. Simulation results show that the proposed model realizes reliable and accurate assessment of transient stability and it has the advantages of short assessment time with less complex model structure to leave time for emergency control.In order to achieve rapid TSA, a large number of machine learning algorithms such as the BP neural network [12], support vector machine [13,14], decision tree [15], random forest [16], and K-nearest neighbor [17] are applied in intelligent systems, such algorithms mainly use the key features of the power system after feature selection to establish functional relationship with transient stability.Once the fault is cleared, the transient stability assessment can be performed, but there is no guarantee of 100% accuracy of assessment. Therefore, an adaptive assessment method [9,18] has emerged in recent years. By determining the time window of the fixed length after the fault, m data sampling points in the time window is used for training; the assessment is performed in chronological order until the assessment confidence meets the requirements. Such approaches guarantee the correctness of assessment, but the assessment time is long and the construction of the model is very cumbersome: m data sampling point means that m classifiers need to be trained. Although the authors of a past paper have [18] considered the influence of historical information on the current time assessment in the time series, it reduces the assessment time to a certain extent, but still needs to train a large number of classifiers.Aiming at solving the problems existing in the above adaptive assessment method, the main contribution of this paper is to proposes a stacked-GRU based intelligent TSA model, which realizes the parameter sharing at each moment through stacked-GRU and utilizes the time series data after the power system failure to train with less complex model structure. The offline training is performed to obtain the optimal parameters. When the application is online, it is judged whether the current assessment result satisfies the confidence level at the time of fault clearing, otherwise measurements will continue to ...

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In the large power grid system, the disturbance arising from any fault will cause great influence to the entire grid, in severe cases, it may cause a disastrous consequence--blackouts or even the collapse of the whole network. This article according to the current power grid technology, perform an analysis to respond to problems during sudden disasters and technical constraints, through sorting distributed power technology, propose the significance of distributed power grid after the accident to ensure the social basic load operation, and clarify the scheduling principle and management mechanism of small distributed power in disaster conditions. Eventually, through the discussion of the social basic load classification, put forward the management mechanism of important user self-provided distributed emergency power when disaster happening.

This paper made a research on the Intelligent Optimization Operating Modeling of Pumped Storage Power Station in Hunan Power Grid. First it introduces the characteristics of Hunan power grid and analysis the practical requirement of dispatching. Then it brings forward the intelligent optimization model and set up running model for pumped storage power station of Hei Mi-feng. At last, it introduces the application of pumped storage power station in Hunan power grid and proves the effectiveness of the optimization models.