期刊
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 13, 期 3, 页码 1607-1619出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2022.3167531
关键词
Hybrid power systems; Uncertainty; Load flow; Correlation; Probabilistic logic; Voltage; Computational modeling; Probabilistic power flow; scaled unscented transformation; boundary inverse transformation; AC; DC hybrid grids; Pearson correlation
资金
- National Natural Science Foundation of China [52177071]
- National Natural Science Foundation of China for International Cooperation and Exchanges [51861145406]
In this paper, a scaled unscented transformation (SUT)-based probabilistic power flow (PPF) method is proposed for addressing the boundary issue of high-dimensional random input variables in AC/DC hybrid grids. The effectiveness of the proposed method is validated using a set of test results on the modified IEEE 1354-bus (PEGASE) system.
In practical AC/DC hybrid grids, the uncertainty sources such as wind speeds and loads are massive and bounded intrinsically, the latter feature of which is neglected in most probabilistic power flow (PPF) analyses unfortunately. In this paper, a scaled unscented transformation (SUT)-based PPF on the large AC/DC hybrid grids, in particular for addressing the boundary issue of these high-dimensional random input variables under Pearson correlation, is proposed and investigated. The empirical formula used for determining the scaling parameter of the SUT method is designed to obtain the sample points, with a purpose of capturing sufficient probability information from the preliminary standard normal distributions. Boundary inverse transformation (BIT) is developed to transform these samples into the original probability space via handling each dimensional boundary value, and to guarantee that all the sample points of SUT fall into a reasonable, physical interval. The effectiveness and advantage of the proposed method are validated by using a set of test results on the modified IEEE 1354-bus (PEGASE) system.
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