Dynamic Capacity Expansion with Planning Method for Distribution Networks Based on Energy Storage

To address the dual overload issues of bidirectional power flows in distribution transformers and lines caused by high photovoltaic (PV) penetration in distribution networks, this paper proposes a dynamic capacity enhancement planning method based on energy storage systems (ESS). First, clustering algorithms are employed to identify typical daily load profiles and their occurrence frequencies. Subsequently, a bi-level model for ESS-based dynamic capacity enhancement planning is developed. The upper level determines the optimal ESS allocation and placement within the distribution network, while the lower level minimizes operational costs under the proposed scheme. An evolutionary algorithm is introduced to solve the upper-level model, and a nonlinear programming solver is used for the lower-level nonlinear optimization problem. Finally, simulations are conducted on the IEEE 33-bus system, with a comparative analysis against traditional transformer and feeder upgrades. Results validate the feasibility and economic efficiency of the proposed method.