Structure-Preservation Model Aggregation for Two-Stage Inverters Based Large-Scale Photovoltaic System
Yang Han, Xiangyang Lin, Ping Yang and 3 more
IEEE Access · 2020
doi:10.1109/access.2019.2962303 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
With the increasing penetration level of large-scale photovoltaic (PV) generator connected to the grid, an accurate simulation model is required for the dynamic analysis of the PV system. However, the detailed electromagnetic simulation of the large-scale system is complex and the dynamic response capability is estimated with obstacle caused by large computational burdens. Therefore, a precise dynamic aggregated model is indispensable for the displacement of the large-scale PV system. The structure-preservation based aggregated model with comprehensive equivalent parameters for large-scale PV system is proposed in this paper. A complete two-stage PV system model is established to analyze the dynamics of the system. Then, the aggregation method is obtained by comparing the dynamic equations of the detailed model with the aggregated model, which is based on the energy relationship in the PV system. Furthermore, four different case studies are considered including the aggregation of identical and different ten parallel-connected PV units both under the same irradiance condition, and the aggregation of different ten parallel-connected PV units under different irradiance and weak grid scenarios, where the aggregation models are obtained through the proposed equivalent modeling method. Finally, the effectiveness of the proposed aggregation method is verified by the simulation results from PSCAD/EMTDC platform, and the consistency between the aggregated model and the detailed model is confirmed under different disturbances of irradiance variation, and continuous symmetric and asymmetric grid faults.
Abstract licence: CC BY-NC-ND
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.