Frequency Response of PV Inverters Toward High Renewable Penetrated Distribution Networks
Article
Article Title | Frequency Response of PV Inverters Toward High Renewable Penetrated Distribution Networks |
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Article Category | Article |
Authors | Bai, Feifei (Author), Cui, Yi (Author), Yan, Ruifeng (Author), Saha, Tapan Kumar (Author), Gu, Huajie (Author) and Eghbal, Daniel (Author) |
Journal Title | CSEE Journal of Power and Energy Systems |
Journal Citation | 8 (2), pp. 465-475 |
Number of Pages | 11 |
Year | 2022 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
China Electric Power Research Institute | |
Place of Publication | China |
Digital Object Identifier (DOI) | https://doi.org/10.17775/CSEEJPES.2021.08470 |
Web Address (URL) | https://www.sciopen.com/article/10.17775/CSEEJPES.2021.08470 |
Abstract | Substantial usage of electronic-based renewable energy resources has completely changed the dynamic behaviours and response time of power networks, which are now fundamentally different from traditional power networks dominated by Synchronous Generators (SGs). This paper evaluates the dynamic response of small-scale Photovoltaic (PV) inverters, which dominate the distribution networks and influence the dynamics of the entire power grid. Recently, some critical events which occurred in Australia have shown that the dynamic responses of small-scale inverters do not always follow the inverter standards. Subsequently, these uncertainties make PV inverters’ response unpredictable and have the potential to threaten the security of power networks. The detailed investigation of the dynamic response characteristics of small-scale PV inverters to grid disturbances is lacking in the current literature. This paper presents new findings from experimental testing under extensive network disturbance scenarios. Furthermore, a data-driven method is proposed to accurately describe the dynamics of solar PV subjected to various frequency disturbances. The results provide beneficial insight to the network operators in predicting power system response to extreme disturbances and avoiding potential grid instability issues, which will assist in achieving 100% penetration of power electronics-based renewable energy resources in the future. |
Keywords | Deep learning, distribution networks, dynamic response, distributed PV, load modelling, PV inverter |
ANZSRC Field of Research 2020 | 400808. Photovoltaic power systems |
400803. Electrical energy generation (incl. renewables, excl. photovoltaics) | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Queensland |
Australian Energy Market Operator, Australia | |
Energy Queensland, Australia | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q7vzw/frequency-response-of-pv-inverters-toward-high-renewable-penetrated-distribution-networks
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