基于MEMD-MMFE的双馈风电场送出变压器励磁涌流识别方法

Identifying Inrush Current for Wind Farm Outgoing Transformer Based on MEMD-MMFE

双馈风电场低电压穿越过程中,送出变压器发生内部故障时,差动电流中存在较大的2次谐波,会导致差动保护拒动。该文提出基于多元经验模态分解-多变量多尺度模糊熵(multivariate empirical mode decomposition-multiscale multivariate fuzzy entropy,MEMD-MMFE)的励磁涌流识别方法。该方法首先将电流经过多元经验模态分解,通过判别分解后的余量函数的单调性,确定是否从原函数中去除余量函数;然后对经过处理的原函数进行多变量多尺度模糊熵变换,得到多变量多尺度模糊熵值面积(简称熵值面积);最后通过或逻辑联立判断变压器两侧电流的熵值面积与给定的制动区面积的大小关系来区分励磁涌流与故障电流。以某风电场接入电网为例,对变压器各种运行工况进行仿真研究,并将该文算法与2次谐波制动等算法进行比较,验证提出算法的有效性。

When an internal fault occurs in the wind farm outgoing transformer during the low voltage ride through of the doubly-fed wind farm, there are larger second harmonic in the differential current of the transformer, which can cause the differential protection to be turned down. Based on the multivariate empirical mode decomposition-multiscale multivariate fuzzy entropy(MEMD-MMFE), this paper proposed a method to identify the inrush current. Firstly, the current was decomposed by the multivariate empirical mode. By discriminating the monotonicity of the residual function in the decompositions, whether to remove the residual function from the original function was determined. Then, the multiscale multivariable fuzzy entropy transformation was carried out for the processed original function, and the area of the multiscale multivariate fuzzy entropy value or the entropy area for short was obtained. Finally, the relationship between the entropy of the current on both sides of the transformer and the size of the given brake area was used to distinguish the inrush current and the fault current. Taking a wind farm connected to the main grid as an example, several operating conditions for transformer were investigated. Through comparing with the second harmonic restraint algorithm, the effectiveness of the proposed algorithm in this paper was verified.