
Reduced‐order modelling of solar‐PV generators for small‐signal stability assessment of power systems and estimation of maximum penetration levels
Author(s) -
ElShimy Mohamed,
Sharaf Adel,
Khairy Hossam,
Hashem Gamal
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.0381
Subject(s) - electric power system , photovoltaic system , computer science , maximum power point tracking , reliability engineering , consistency (knowledge bases) , maximum power principle , matlab , stability (learning theory) , grid , power (physics) , control theory (sociology) , control engineering , engineering , electrical engineering , mathematics , voltage , physics , control (management) , artificial intelligence , machine learning , geometry , quantum mechanics , inverter , operating system
There is an urgent need for constructing adequately accurate standard reduced‐order models of various renewable sources for fast assessment of the stability and security of power grids. This study focuses on this theme considering solar‐photovoltaic generators (SPVGs). The main objectives of this study include the construction of a valid reduced‐order dynamic model for SPVGs, analysis of the impact of the SPVG model on the stability of the host power system in a mixed mode generation under various integration scenarios, and evaluation of the consistency of SPVGs with fault‐ride through requirements based on relevant grid codes. Various modes of operations of SPVGs are analysed and considered using an enhanced search algorithm for maximum power point tracking. In addition, this study proposes an algorithm for the estimation of the maximum penetration level of SPVGs constrained by the small‐signal stability of power systems. The results presented in this study are based on dynamic simulation and validation using the MATLAB, PSAT, and ETAP‐software environments for stability assessment of power systems. The results show that the developed reduced‐order model indicates an acceptable accuracy accompanied with simplicity in simulating complex dynamic performances of host power systems with SPVGs integration.