Lightning risk assessment model for transmission lines with lift-based improved analytic hierarchy process

Abstract

This paper proposes a new assessment method for lightning trip-out of transmission lines that includes an improved analytic hierarchy process (IAHP) algorithm based on a lift in association rules. First, the k-means clustering algorithm is used to discretize the geomorphic information along transmission lines, and ten feature factors are obtained. Next, by analysing the correlation between each feature factor and a lightning trip-out event using the lift algorithm, the strong correlation factors are extracted. On this basis, an IAHP algorithm optimized by lift is proposed to establish an objective judgment matrix. Then, multiple indexes are combined as a criterion layer of the IAHP, and a lightning risk assessment model of transmission lines is established. Finally, the proposed method is validated by simulations using 28 transmission lines with 220 kV voltage grade of a provincial power grid of China. An assessment model is established using the lightning trip-out data in the period 2010–2014, and then this model is employed to estimate the lightning trip-out risk in the period 2015–2018. Based on the number of phase faults, the agreement between the estimation results and the actual values is 76%. The proposed model provides a new method for the lightning risk assessment of transmission lines.