A Fault Identification Method for Microgrid Considering Photovoltaic Power Intermittency

doi:10.12204/j.issn.1000-7229.2020.09.009

Abstract

Abstract:

In the islanded microgrid integrated with high proportion of photovoltaic power, the change of solar irradiance will lead to obvious photovoltaic power fluctuation, and then affect the trend of fault current of lines in microgrid. For the photovoltaic power with different irradiance, how to accurately identify the microgrid fault is important for microgrid protection. To this issue, a typical microgrid model with photovoltaic power generation is firstly established in this paper, and the influence of solar irradiance variation on the fault current in the islanded microgrid mode is analyzed. Then, the fast wavelet energy entropy (WEE) algorithm is used to extract the transient characteristics of fault current, and the concise transient characteristics are selected to construct the fault comprehensive sample set. Finally, considering photovoltaic power intermittence, this paper forms a new microgrid fault identification method by training Kernel-based extreme learning machine with typical fault sample set. The simulation result shows that the proposed method can not only accurately extract the transient characteristics of microgrid fault under different irradiance, but also accurately identify the fault, which provides technical support for the fault analysis and protection of microgrid.

Key words: microgrid, photovoltaic power generation, fault identification, feature extraction, fast wavelet energy entropy (WEE) algorithm

CLC Number:

TM773

LI Haoru, DING Baodi, JI Yu, WANG Yonggang, CHEN Jikai, ZHANG Liwei. A Fault Identification Method for Microgrid Considering Photovoltaic Power Intermittency[J]. ELECTRIC POWER CONSTRUCTION, 2020, 41(9): 76-85.

Figures/Tables 17

Fig.1 Microgrid system with photovoltaic power generation and energy storage

Fig.2 Currents during two-phase grounding short-circuit fault under different irradiations

Fig.3 Currents during phase-to-phase short-circuit fault under different irradiations

Fig.4 Current vectors at phase-to-phase metal short-circuit fault point

Fig.5 Current vectors at two-phase metal short-circuit grounding fault point

Fig.6 Forward wavelet transform using lifting scheme

Fig.7 Transient characteristics of single-phase grounding fault current in Line S1

Fig.8 Transient characteristics of two-phase short-circuit fault current in Line S1

Fig.9 Transient characteristics of two-phase grounding short-circuit fault current in Line S1

Fig.10 Transient characteristics of operating current during sudden change of load L2

Fig.11 Transient current characteristics comparison of single-phase grounding fault in different sections

Fig.12 The procedure of PSO-based KELM for fault identification

Fig.13 Fitness curve of PSO for KELM parameter optimization

Table 1 Comparison of the fault classification accuracy

Table 2 Fault classification accuracy under different PV irradiance%

Table 3 Comparison of the fault section identification accuracy

Fig.14 Comparison of accuracy distribution of the fault section identification

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