A hierarchical evaluation method for power quality of microgrid cluster based on multi-temporal and spatial scales fusion analysis

Abstract

The power quality (PQ) assessment for microgrid cluster (MGC) is essential for management. However, there is a lack of in-depth exploration and refinement on how to conduct a hierarchical assessment of the PQ for MGC on multi-temporal and spatial scales. To address the above issues, a novel hierarchical assessment method on multi-temporal and spatial scales is innovatively proposed in this paper. Firstly, on the time scale, the principal component kernel density estimation (PCA-KDE) fusion analysis, improved criteria importance through intercriteria correlation kernel density estimation (CRITIC-KDE) fusion analysis, and transgressive kernel density analysis are employed to capture the long-term trend, short-term changes, and fast response of PQ, respectively, and quantify its uncertainty and volatility through the standard deviation (SD) of the kernel density function. Furthermore, on the spatial scale, the assessment structure and the logical connection between the levels are clarified, and the PQ localization is realized by combining the multi-timescale assessment results with the spatial structure of MGC. Finally, examples show that compared with traditional methods, the uncertainty of PQ of MGC in the proposed method is fully revealed from multiple dimensions. The PQ index exceedance rate is increased to 50 % or 83 % on ultra-short scale, the evaluation score is reduced by about 10 % on short time scale, and the PQ score is reduced by about 15 % on long time scale, providing more reasonable decision support for the management of MGC.