
Two‐step method for identifying photovoltaic grid‐connected inverter controller parameters based on the adaptive differential evolution algorithm
Author(s) -
Liu Zhongqian,
Wu Hongbin,
Jin Wei,
Xu Bin,
Ji Yu,
Wu Ming
Publication year - 2017
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.2017.0572
Subject(s) - photovoltaic system , inverter , computer science , controller (irrigation) , grid , differential evolution , control theory (sociology) , algorithm , differential (mechanical device) , mathematics , engineering , electrical engineering , control (management) , artificial intelligence , voltage , biology , geometry , aerospace engineering , agronomy
Photovoltaic (PV) grid‐connected inverter is the core component of PV generation system; quickly and accurately obtaining the parameters of inverter controller has great significance in analysis of transient characteristics of PV generation system. Parameter identification relies on disturbance signals and measurements selection, and the trajectory sensitivities of inverter controller parameters are calculated with different system outputs as the measurements, the disturbance signals include AC three‐phase short‐circuit fault and DC voltage reference jump, accordingly, a two‐step identification method is proposed, the first step use a three‐phase fault to identify all voltage loop parameters and the proportional coefficient of current loop, and the second step consider a DC voltage reference jump disturbance to identify the integral coefficient of current loop and the setting inductance value. The adaptive differential evolution is taken as the identification algorithm, which adopts adaptive strategies for algorithm parameters in order to speed up the convergence and enhances the balance between the global search and local mining. The simulation analysis validates the effectiveness of this method. In addition, the impact of the inductance error on the identification is discussed.