In the context of building a new type of power system, the optimal operation of high-proportion new-energy distribution networks (HNEDNs) is a current hot topic. In this paper, a stochastic distribution robust optimization method for HNEDNs that considers energy-storage refinement modeling is proposed. First, an energy-storage lifetime loss model based on the rainfall-counting method is constructed, and then an optimal operation model of an HNEDN considering energy storage refinement modeling is constructed, aiming to minimize the total operation cost while taking into account the energy cost and the penalty cost of abandoning wind and solar power. Then, a source-load uncertainty model of HNEDN is constructed based on the Wasserstein distance and conditional value at risk (CvaR) theory, and the HNEDN optimization model is reconstructed based on the stochastic distribution robust optimization method; based on this, the multiple linearization technique is introduced to approximate the reconstructed model, which aims to both reduce the difficulty in solving the model and ensure the quality of the solution. Finally, the modified IEEE 33-bus power distribution system is used as an example for case analysis, and the simulation results show that the method presented in this paper, through reducing the loss of life in the battery storage device, can reduce the average daily energy storage depreciation cost compared to an HNEDN optimization method that does not take the energy storage life loss into account; this, in turn, reduces the total operating cost of the system. In addition, the stochastic distribution robust optimization method used in this paper can adaptively adjust the economy and robustness of the HNEDN operation strategy according to the confidence level and the available historical sample data on new energy-output prediction errors to obtain the optimal HNEDN operation strategy when compared with other uncertainty treatment methods.

To address voltage violation issues in active distribution networks, this paper proposes a reactive power optimal configuration method that considers the dynamic voltage regulation strategy of a unified power quality conditioner (UPQC). First, an adaptive network partitioning model based on reactive power–voltage modularity is developed. This model identifies high-sensitivity regions and determines preferred siting locations for UPQCs. Next, a voltage stability index is derived using a two-bus equivalent decoupled model. The classical holomorphic embedding method is then applied to track the variation in the voltage stability index, with respect to the embedding factor. Based on these results, weak buses are identified as key buses for evaluating the effectiveness of voltage control measures. Subsequently, a bi-level optimisation model that integrates planning and operation is formulated by incorporating the dynamic voltage regulation strategy of the UPQC. The model aims to minimise the equivalent annual total cost of the deployment scheme while reducing bus voltage deviations, thereby enabling proactive mitigation of voltage violations in active distribution networks. Finally, case studies conducted on an extended IEEE-33 bus power system and real-world distribution networks demonstrate that the proposed UPQC optimal configuration method effectively alleviates voltage violation problems.