A comprehensive state-space model of two-stage grid-connected PV systems in transient network analysis. (September 2019) - Levis, Colin; O'Loughlin, Cathal; O'Donnell, Terence; Hill, Martin
Highlights: A dynamic linear state-space model of a two-stage photovoltaic system. Verified linear state-space model using power hardware in the loop. Provides a validated accurate and efficient photovoltaic system model. Studies high penetration levels of geographically distributed photovoltaic systems. Analyses dynamic interactions with the low voltage distribution network. Abstract: The large-scale deployment of distributed photovoltaic (PV) systems on the low voltage distribution network (LVDN) poses significant challenges to network operators related to the dynamic interactions of the PV systems and the network. To address these challenges and implement grid support services (GSS's), accurate and efficient PV system models are required that allow large networks with integrated PV to be simulated in an economical time frame. For this purpose, an accurate, computationally inexpensive, linearised, state-space model of a two-stage PV system in the dq0 rotating reference frame is presented in this paper. The model includes both the DC/DC and DC/AC converters, all system controllers, parasitic components, system losses, and an efficient PV array model. The performance of the model is validated with measured experimental data from a power hardware in the loop (PHIL) testbed at various simulated step changes in irradiance. The developed model is applied to a modified radial European LVDN benchmark with multiple distributed PV systems to demonstrate some of the functions, applications and advantages. A combined active and reactive power voltage-dependent droop control characteristic for GSS's is demonstrated with solar irradiation step changes and measured solar irradiation data applied to each PV system. A full electromagnetic transient (EMT) PV system model developed in MATLAB is presented and compared to the linear state-space (LSS) model. The results demonstrate a computational burden reduction of 116:1 without loss of accuracy providing significant benefits and functionality for the study of large-scale grid integration of PV systems.