Impact analysis of a planning-grade DER digital-twin-ready model of a real distribution feeder in a high-fidelity simulation environment
Article
Iqbal, H, Sarwat, A. (2026). Impact analysis of a planning-grade DER digital-twin-ready model of a real distribution feeder in a high-fidelity simulation environment
. 31 10.1016/j.ecmx.2026.101978
Iqbal, H, Sarwat, A. (2026). Impact analysis of a planning-grade DER digital-twin-ready model of a real distribution feeder in a high-fidelity simulation environment
. 31 10.1016/j.ecmx.2026.101978
Distribution feeders are increasingly hosting distributed energy resources (DERs) such as solar photovoltaics (PV), electric vehicles (EVs), and battery energy storage systems (BESS), yet empirical assessments that jointly address hosting capacity, probabilistic risk, and harmonic compliance on real utility networks remain scarce, most studies rely on synthetic test feeders and omit one or more of these evaluation dimensions. This paper integrates established analysis methods, deterministic base-case evaluation, spectrum-based harmonic analysis, nodal PV hosting-capacity mapping, and time-series Monte Carlo assessment, into an automated pipeline applied to a real distribution feeder in Miami, USA. An ADMS-to-OpenDSS conversion module processes 11,376 electrical assets in 36.23 s with automated topology validation and parameter completion, producing a simulator-ready three-phase unbalanced model spanning voltage classes from 69 kV to 120 V. Deterministic nodal sweeps across 112 eligible load buses yield a mean PV hosting capacity of 26.4 kW with a maximum of 336 kW, while harmonic-limited hosting capacity exhibits a median of 25.2 kW and a P90 of 126.0 kW under an 8% voltage THD screening limit, demonstrating that harmonic constraints materially compress allowable PV at the majority of connection points. Monte Carlo simulations (500 realizations per penetration level, 0%–75% in 5% increments) with annual 8760-hour quasi-static time-series resolution reveal that PV-only adoption maintains voltage compliance within the 0.95–1.05 p.u. band and reduces system losses, whereas joint PV+EV+BESS deployment preserves hard constraint feasibility but increases peak demand and widens the operating envelope due to EV-driven coincident loading. All analysis pipelines are implemented in Python with reproducible seeding and parallel execution; the automated conversion pipeline is repeatable for other ADMS exports, though the empirical findings reported here are specific to the studied feeder.
