Summary To reduce the investment cost of voltage sag mitigation equipment and the probability of voltage sag at the installation nodes of sensitive load, a comprehensive voltage sag mitigation strategy based on sensitive load clustering is proposed. The Monte Carlo method is used to get the stochastic estimation model of voltage sag to determine the lines with high fault probability, so as to get the weak links in the power grid, that is, the voltage sag vulnerable area. This paper proposes four sensitive indicators called tolerance magnitude of voltage sag, endurance duration of voltage sag, equipment capacity, and power dependence. The weight of each indicator is determined by the combination weighting method, and the affinity propagation (AP) clustering algorithm is used to classify different sensitive loads. The sensitive loads are mitigated by installing the energy storage equipment and dynamic voltage restorer (DVR), and the energy storage capacity is configured with the goal of minimum life cycle cost under the premise of voltage compensation. The result using MATLAB/Simulink and the laboratory equipment shows that, compared with existing mitigation strategies, the proposed mitigation strategy can not only effectively reduce the investment cost and the probability of voltage sag but also make the voltage distribution more reasonable.

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