Loss prediction method for large-scale wind power-accessed power grid
A technology that is connected to the power grid and a prediction method is applied to electrical components, circuit devices, AC network circuits, etc., and can solve problems such as inability to effectively take into account node injection power fluctuations and low network loss prediction accuracy
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Embodiment 1
[0026] figure 1 It is a flow chart of the network loss prediction method after large-scale wind power is connected to the grid. figure 1 , the network loss prediction method provided by the present invention after the large-scale wind power is connected to the power grid includes:
[0027] Step 1: Input the system data and wind farm data, including the rated power of the wind turbine, the rated wind speed of the wind turbine, the wind speed, the cut-in wind speed, the cut-out wind speed, the wind speed distribution parameters, the active output of the generator set, and the normal operation of the generator set. probability, the active output value of the generator set during normal operation, the expected value of the load active power, the variance of the load active power and the load active power value; the wind speed distribution parameters include shape parameters, scale parameters and location parameters.
[0028] Step 2: Determine the probability distribution curve of...
Embodiment 2
[0067] According to the above method, this embodiment adopts the following figure 2 The IEEE 30 node system shown ( figure 2 is the system wiring diagram) as the verification model, the analysis is as follows:
[0068] It is assumed that the wind farm is connected to the 29th node of the IEEE30 power-saving system through the transformer and the 110kV line, and the line parameter of the wind farm connected to the system is 12.6+j24.96Ω. Then the mathematical expectation of the injected power of each node of the system can be obtained from the probability distribution curve of the output of the wind farm, the output of the generator and the load, as shown in Table 1.
[0069]
[0070] Table 1: Mathematical expectations of injected power at each node
[0071] By calculating the semi-invariant of the network loss power, and using the Gram-Charlier series expansion to obtain the network loss probability distribution curve ( image 3 ), it can be seen that the network loss ...
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