P–V Curve-Based Pre-Screening for Inverter-Interfaced ESS Siting Using a Dynamic-Impedance-Informed Static Model

Rapid pre-screening of inverter-interfaced energy storage system (ESS) connection locations remains challenging in planning studies for power systems with high renewable penetration and converter-interfaced ESSs. Active-power–voltage (P–V) curve analysis provides an efficient tool for this task, but the reliability of its screening results depends on how the converter-related voltage-support behavior of the ESS is represented in the static equivalent model. This paper develops a planning-stage ESS siting pre-screening workflow by incorporating existing dynamic-impedance equivalent results into the ESS static model and embedding the corrected model into target-bus P–V scans. An indicator P0.85 is defined as the load level at which the target-bus voltage reaches a representative low-voltage boundary of 0.85 pu and is used to quantify the local load-growth margin. A P0.85-based improvement matrix and comprehensive ranking indices are then constructed to compare voltage-margin improvements of different candidate ESS connection locations. Steady-state electromagnetic transient (EMT) operating points are used to evaluate voltage approximation errors and cross-check the improvement ranking trend. In the IEEE 39-bus test system, the scalar-form and complex-form dynamic-impedance-corrected static models reduce the mean absolute voltage error by approximately 57.7% and 59.1%, respectively, compared with the connection-branch impedance model. The first-tier candidate buses obtained from the static pre-screening are consistent with the EMT-interpolated ranking trend. A supplementary IEEE nine-bus case further illustrates the feasibility of applying the proposed procedure under a different network topology. The main contribution lies in integrating existing dynamic-impedance equivalents with a P0.85-based ESS siting pre-screening framework for candidate-set reduction before detailed EMT studies and engineering assessment rather than final ESS siting optimization.