School of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China
This work is supported by National Natural Science Foundation of China (No. 51407113) and Shanghai Engineering Research Center of Green Energy Grid-Connected Technology (No. 13DZ2251900).
In recent years, due to the influence of extreme weather, the rate of large-scale blackouts in distribution networks has been raised, and the resilient distribution network that can resist natural disasters and reduce the impact of power failure accidents has attracted people’s attention. In order to better evaluate the resilience of distribution network to extreme disasters, a method for evaluating the resilience of smart distribution network is proposed. Firstly, a fault model in extreme weather is established to quantify the influence of extreme weather on the distribution network. Secondly, in view of the randomness of extreme weather, Monte Carlo simulation of extreme weather scenarios is adopted and K-means clustering algorithm is applied for scenarios reduction. Time-varying failure rate of each branch of distribution network can be obtained according to the vulnerability curve. Considering the uncertainty of load and renewable energy, Latin hypercube sampling is adopted to extract load, renewable energy and distribution network fault scenarios to evaluate the resilience of distribution network. Then, in order to fully and accurately reflect the resilience of distribution network with distribution generator, the distribution network is divided into two stages of disaster prevention and reductionwhen suffering from natural disaster. Based on this, index system of resilience evaluation is constructed contains defense time of distribution network, coefficient of resilience recovery, coverage rate of island sustainable time and mean interruption time of critical load. Finally, the simulation evaluation of the resilience of an actual distribution system with two feeders is carried out, and the influence of power line type, photovoltaic permeability rate and tie lines on the resilience of the distribution network is considered, which verifies the effectiveness of the proposed evaluation method.
LI Zhenkun,WANG Fashun,GUO Weiyi,et al.Resilience Evaluation of Smart Distribution Network in Extreme Weather Condition[J/OL].Automation of Electric Power Systems,http://doi.org/10.7500/AEPS20190418008.