Improving Distributed Network Resilience with Energy Storage: An Optimal Planning Strategy Based on Subjective and Objective Weight Method

The integration of large-scale distributed photovoltaics (PVs) has improved the conventional resilience of distribution networks to a certain extent, but it has also made the power quality problems of distribution networks more prominent under steady-state operation. At the same time, the increase in the proportion of sensitive loads has also made the impact of voltage sag events increasingly serious, resulting in equipment damage and significant economic losses on the user side due to power quality problems when the conventional resilience assessment results of distribution networks are high. Based on this, this paper proposes an optimal planning strategy for improving the resilience of distributed networks based on subject and objective weight method. Firstly, for the proposed resilience assessment indicators, the improved Analytic Hierarchy Process (AHP) is used to calculate the subjective weights of the indicators, and the entropy weight method is used to calculate the objective weights of the indicators. The optimal weight combining subjectivity and objectivity is obtained comprehensively. Secondly, by combining the proposed resilience and power quality indicators, a comprehensive resilience indicator objective function is established. Based on the second-order cone linearization method, a multi-objective energy storage (ES) optimization configuration model with the lowest daily operation cost and the optimal comprehensive resilience of the distribution network is established. Finally, based on IEEE 33 node simulation, the comparison of calculation examples shows that the proposed energy storage optimization configuration model can effectively reduce system economic costs, while improving the resilience and power quality level of the distribution network.