Dynamic probabilistic power flow (PPF) calculating method considering wind speed predication error temporal-spatial coherence
A dynamic probabilistic power flow, spatiotemporal correlation technology, applied in computing, AC network circuits, instruments, etc., can solve problems such as large kurtosis and skewness, ignoring wind speed timing, reducing wind speed uncertainty, etc.
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Embodiment 1
[0065] Take the IEEE14 node system as an example, such as figure 2 As shown, wind farms with a rated power of 50MW are added to the nodes 10, 11, 13 and 14 of the system respectively. The fans are all operated with a constant power factor of 1, and the cut-in wind speed, rated wind speed and cut-out wind speed of the fan are respectively taken as 3m / s, 12m / s and 22m / s. Assuming that the actual power error of the wind farm obeys a normal distribution with zero mean, its probability density function is as follows:
[0066] f [ P ϵ ( v ) ] = 1 2 π · ( αv ) exp [ - ( P ϵ ...
Embodiment 2
[0077] Taking IEEE118 nodes as an example, wind farms with a rated power of 50MW are added to nodes 20, 35, 38 and 51 respectively. The wind farm and wind speed model are the same as those in Example 1. On the basis of the original load, the active load of 200MW is increased proportionally, and the load model is the same as Section 3.1. Considering the spatial correlation of active load prediction errors among nodes 2, 3, 4, and 5, the spatial correlation coefficient of load prediction errors at different locations is 0.5, and the value of time correlation is the same as that in Embodiment 1.
[0078] Such as Figure 8 As shown, the obtained dynamic probability distribution curve of active power between branches 19-20. Such as Figure 9 As shown, there are 500 sample function curves of active power between branches 19-20.
[0079] From Figure 8 and Figure 9 It can be seen that the DPPF calculation based on LHS can obtain the dynamic characteristics of the branch power ...
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