Telemetry-Only Voltage Sensitivity Estimation for Interoperable DER Aggregation

초록

Voltage-to-power sensitivity information is a key enabler of voltage regulation, distributed energy resource (DER) dispatch, and inverter-based control in distribution systems with high photovoltaic (PV) penetration. However, practical operators, such as aggregators and virtual power plants, often lack access to full-feeder models or feeder-wide phasor measurement unit (PMU) infrastructure. This study proposes a telemetry-only deep-learning framework to estimate voltage sensitivities using interoperability-enabled DER telemetry without assuming feeder-wide PMU deployment. The method first learns a telemetry-to-voltage surrogate, and then calibrates its Jacobian using sparse finite-difference teacher sensitivities from representative operating points. Thus, the estimator reconstructs the voltages while preserving the local voltage-sensitivity structure required for operational use. The framework was validated on three feeders spanning near-linear to strongly nonlinear voltage behaviors-the IEEE 37-bus, IEEE 123-bus, and IEEE European Low-Voltage (LV) test feeders-using six years of irradiance-driven time-series simulations coordinated through a MATLAB-OpenDSS COM interface. The proposed zero-PMU estimator was compared with PMU-less baselines across these feeders (Case 1); the robustness to PV penetration was examined (Case 2); and the cost-accuracy trade-off was evaluated by adding some strategically placed PMUs (Case 3). The proposed method shows a linearity-dependent advantage that grows with feeder nonlinearity-competitive on the near-linear 37-bus feeder, while reducing the sensitivity root mean square error by approximately 4.3 times over the best linear baseline on the nonlinear LV feeder-and sustains this accuracy across penetration levels, whereas limited PMU augmentation yields further deployment-stage-dependent gains.

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