Adjustment Strategies Based on Improved Apriori Algorithm for Overloaded Transmission Section in Receiving-End Power Grid Under UHVDC Blocking Fault

doi:10.12204/j.issn.1000-7229.2020.09.011

Abstract

Abstract:

Once blocking fault occurs in large-capacity ultra-high-voltage direct current (UHVDC) transmission system, a series of control measures are implemented to fill the power shortage of the receiving-end power grid. Focus on the problem of overloaded transmission sections after primary and secondary frequency modulation, this paper proposes an overloaded-section adjustment strategy based on the improved Apriori algorithm. Firstly, the blocking fault is simulated by the dynamic power flow algorithm and the transmission sections are adjusted by sensitivity method. Then, the adjustment information is extracted. After data processing, the database of unit, load adjustment strategy and section state change is set up. The Apriori algorithm is improved that fore-part item-set is restricted to be the unit and load adjustment strategy and rear-part item-set is restricted to be the change of the section state. The strong association rules between the adjustment strategy and the change of the section state are analyzed by improved Apriori algorithm. Finally, the simulation results of Jinping-Suzhou DC fault and association analysis show that the improved Apriori algorithm greatly reduces the generation of invalid rules, and the strong association rules effective for section adjustment are extracted from association analysis, which provides decision-making basis for overloaded transmission section adjustment of the power grid.

Key words: DC blocking fault, transmission section overload, improved Apriori algorithm, adjustment strategy

CLC Number:

TM712

GUO Kai, HAN Yi, WANG Yan, QI Xiaolin, YE Haifeng, JIN Yifang, MA Xiaochen, TAO Lei. Adjustment Strategies Based on Improved Apriori Algorithm for Overloaded Transmission Section in Receiving-End Power Grid Under UHVDC Blocking Fault[J]. ELECTRIC POWER CONSTRUCTION, 2020, 41(9): 94-101.

Figures/Tables 9

Fig.1 Flow chart of improved Apriori algorithm

Fig.2 Flow chart of association analysis

Fig.3 Receiving-end power grid of Jinping-Suzhou DC transmission system

Fig.4 Comparison of the number of association rules

Table 1 Part of strong association rules

Fig.5 Confidence distribution of different databases

Table 2 Part of association rules between sections

Table 3 Part of adjustment results of overloaded sectionsMW

Table 4 Part of strong association rules of Shipai-Cheyu section

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