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Keywords

renewable energy station;uncertainty optimization;reactive power optimization;sample robust optimization; Nataf transformation;correlation distribution

Abstract

With a large number of renewable energy stations connected to power grid, their stochastic power outputs have a great impact on the reactive power and voltage control of power system. To this end, a sample robust reactive power optimization approach is proposed considering the power output uncertainty of renewable energy stations. Firstly, considering the variation of generator active power output caused by the random output fluctuation of renewable energy stations, an uncertain reactive power optimization model of power system is established. Secondly, based on the sample robust optimization method, the optimization model is transformed into a two‑level optimization model. The upper‑level model searches for the generator terminal voltages, transformer ratios and number of shunt capacitor switching groups that minimize the active power network loss under the average worst‑case scenario. The lower‑level model searches for the worst scenario in the box uncertainty set near each sample point. Next, in order to consider the correlation between the power output of the same type of renewable energy stations, the sample points in the independent normal space are transformed into the sample points in the relevant original sample space by using the relationship between Nataf transform and its inverse transform. Then, the column and constraint generation algorithm is used to solve the two‑layer optimization model alternately and iteratively. Finally, through the analysis and calculation of the modified IEEE 39 bus system and the actual Guizhou power grid, the correctness and effectiveness of the proposed method is verified.

DOI

10.19781/j.issn.1673-9140.2023.02.010

First Page

84

Last Page

95

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