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Weak Link Identification in Active Distribution Network Based on Probabilistic Load Flow

2019 IEEE Sustainable Power and Energy Conference (iSPEC)(2019)

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摘要
The randomness and uncertainty of distributed generators and multiple loads have brought severe challenges to the power supply reliability of the distribution network, so it is necessary to effectively identify the weak links which restrict the power transmission capacity. Aiming at this problem, this paper proposes a weak link identification method for the active distribution network (ADN) based on the probabilistic load flow (PLF). Firstly, considering the characteristics of distributed generators’ output and the load variation, a probabilistic load flow algorithm based on point estimation is proposed. Then, considering the constraints such as bus voltage, line capacity and transformer capacity, the weak links of distribution network are identified on the basis of PLF calculation, and the weak degree of power supply in each link is determined by the repeated power flow. Finally, the effectiveness of the method is verified by the IEEE 33- bus distribution system. The simulation results show that the method proposed in this paper can not only quickly and effectively identify the weak links of active distribution network, but also provide a series of power supply bottlenecks, which can further assist dispatchers to take corresponding measures to improve the power supply capacity of ADN.
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