An electrical model-free three-phase OPF for PV-rich LV networks using smart meter and transformer data
Year: 2024
Type: article
Abstract: The growing uptake of residential solar photovoltaic (PV) systems is prompting distribution companies to actively calculate PV inverters’ setpoints to manage voltage and thermal issues in low-voltage (LV) distribution networks. Although the model-driven Optimal Power Flow (OPF) has shown great potential for this purpose, the unavailability of electrical models (e.g., topology) for three-phase LV networks hinders its adoption by distribution companies. To address this, we propose an electrical model-free (independent from LV network models) three-phase OPF approach to calculate the PV inverters’ setpoints. No electrical model is used at any stage, instead a Neural Network is trained solely with historical measurement data (that calculates voltages instead of using power flows) to capture the nonlinear relationships of the LV network. The performance of the proposed approach is assessed using synthetic data considering a realistic Australian residential LV network with 146 customers, part of an integrated MV-LV network with 3,400+ customers. Time-series results demonstrate that the proposed approach has similar accuracy as the state-of-art model-driven OPF (that fully captures the physics) in calculating PV setpoints and almost same overall curtailment. Thus, the proposed approach presents an alternative for distribution companies to manage PV without any LV network models, only historical measurement data.
Source: Electric Power Systems Research
Institution: The University of Melbourne
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,480
OpenAlex ID: W4404733165