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The steady-state time-varying law of the grid state variables caused by load fluctuations is the slow dynamic characteristic of the grid, and the rapid extraction of its characteristics is the basis for the rapid estimation of the large scale grid operation state and the optimization of static stability prevention and control. To solve the computation speed problem of large power grid system state calculation by load prediction multiplied by jacobian inverse matrix, a data-driven slow dynamic characteristic extraction and state estimation method are proposed in this paper. Based on the various characteristics of the PV curve determined by bifurcation theory and continuous power flow, a series of time-varying second-order polynomials of bus voltage is used to represent the slow dynamic characteristics. The estimated operation state can be quickly calculated by short-term historical operating data according to this characteristic. The accuracy and rapidity of the proposed method are demonstrated on several test systems.

Large-scale electric heating heat storage load is of great significance for eliminating wind and abandoning wind. However, power grid dispatching needs to coordinate these different types and different capacity loads so that it does not affect its own safe operation. The grid plays a bigger role. To this end, the large-scale electric heating heat storage load is divided into two categories: one is distributed small capacity; the other is centralized large capacity. The two load operation characteristics are modeled, and a coordinated operation strategy of two loads is proposed. The calculation of the actual data of a provincial power grid shows that the distributed has the characteristics of timing and fixed amplitude, and the centralized has the characteristics of dynamic adjustment. The distributed consumption is the low-level electricity, which can improve the ability to dissipate the wind and improve the peaking capacity of the power grid; most of the centralized consumption is the abandonment of wind power, but also can improve the dynamic peaking ability of the power grid.

Large-scale clean energy is merged into the power grid. For different grid-connected methods, the reasons for wind abandonment are different. In this paper, it studied peak-regulated wind abandonment and grid frame abandoned wind, and proposed the calculation model and discrimination method of the peak-regulated wind abandonment and grid frame abandonedwind; it also proposed the correlation analysis method of power grid wind abandonment, peak-regulated wind abandonment and grid frame abandoned wind. Combined with the example, the paper analyzedthe relationship between power grid wind abandonment, peak-regulated wind abandonment and grid frame abandoned wind. For the northern heating season, the peak-regulated wind power abandonment is larger. In the non-heating season, the grid frame abandoned wind power is larger, and when the peak-regulated wind power abandonment is larger, the grid frame abandoned wind power is smaller, and the duration of the peak-regulated wind abandonment is smaller than the duration of the grid frame abandoned wind. Because a large number of measures to consumption wind are mainly aimed at peak-regulated wind abandonment, the proportion of grid frame abandoned wind has exceeded 1/3 of the total abandoned wind. It can be seen that the research on abandoning wind should be carried out from the two dimensions of peak-regulated wind abandonment and grid frame abandoned wind.

Aiming at the randomness and volatility of the abandoned wind with high proportion wind power connected to the large power grid, this paper proposed a the entire processes accurate evaluation analysis method with multi-dimensional, multi-period and multi-type, constructed a multi-dimensional analysis system such as electricity, hours, abandonment rate and abandonment ratio, and constructed a multi-period analysis system such as the annual, heating season, monthly and hourly electricity distribution and the corresponding low valley period, it also constructed a multi-type analysis system such as peak shaving abandoned wind and grid structure abandoned wind, which provides a theoretical basis for implementing large-scale abandoned wind consumption. Combined with the actual examples, the abandoned wind analysis system established in this paper has practical significance for mastering the law of abandoning wind and selecting appropriate measures for abandoning wind consumption.

On 1st December 2017, the world's largest 100MW/129MWh lithium battery storage power station from Tesla was put into operation in South Australia. Then on 14th December 2017 and 18th January 2018, Tesla storage battery participated in grid frequency recovery after Victorian Loy Yang power station unit tripping accident. Tesla was triggered 140ms after the accident, before injecting active power to the grid. As a result, grid frequency was back to 50Hz with the help of Tesla and other contracted coal-fired generators within 6 minutes. Up to now, Tesla power station has provided auxiliary services such as regular adjustment and output, energy output and emergency output to the power grid. This paper first analyzes the physical and economic reasons why Tesla storage battery is integrated into Australia power grid. Then the structure and control strategy of battery is introduced. The operation of energy storage is introduced from both physical and economic dimensions. Later on, energy storage grid related technical standards and evaluation hierarchy are suggested to be made. New type of ancillary service is developed and storage’ s profit making mode is explored. All above proposals are lessons that China should learn to develop its storage technologies and storage-grid integration technologies.

Statistically, power grid accidents are inevitable. The larger the scale of a power grid, the more probably a power grid accident will occur. Preventing a power grid accident as soon as possible from occurring and handling the accident in a most efficient and quick way are two important topics to power grid dispatchers. This paper analyses in detail the causes of grid accidents such as tripping of above 220 kV lines of Liaoning Power Grid using big data statistics method, and finds some objective laws, which would help Liaoning Power Grid and other power grids in safe operation and scientific management.