Parameter identification of photovoltaic discrete-time equivalent model using the bat algorithm

被引:3
|
作者
Shen, Fu [1 ]
Zhang, Wei [1 ]
Cao, Yang [1 ]
Wang, Zhe [1 ]
Yang, Guangbing [1 ]
Shan, Jieshan [1 ]
Zhai, Suwei [2 ]
机构
[1] Kunming Univ Sci & Technol, Fac Elect Power Engn, Kunming 650500, Peoples R China
[2] Yunnan Power Grid Co Ltd, Elect Power Inst, Kunming 650217, Peoples R China
基金
中国国家自然科学基金;
关键词
PV power; Dynamic equivalence; Bat algorithm; Parameter identification; SIMULATION; CONVERTER;
D O I
10.1016/j.egyr.2023.04.166
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
As the development of photovoltaic (PV) power generation continuously accelerated the total installed capacity of PV, the traditional static load model is difficult to meet the needs of the power grid with the increasing penetration of PV. And the dynamic model of grid-connected PV power generation is complicated and there are plenty parameters need to be identified, so the dynamic model of grid-connected PV power generation are extremely challenging to apply in wide-area power system. In this paper, a discrete-time equivalent model of PV (PDEM) is established based on the third-order dynamic differential equation of the PV power generation system and the parameters of the PDEM are identified using the least squares (LS) and the bat algorithm (BA). Besides, the dynamic characteristics of the PV power generation grid connected system with different permeability and the fitting residuals of the two methods is analyzed in the IEEE14-bus system incorporated into the PV system. The applicability of the PDEM is verified by setting short circuit grounding fault and changing the PV permeability and voltage dip. The simulation results demonstrate that the PDEM has a strong adaptability and good applicability in the case of high PV permeability with a wide application. And the applicability of the BA in identification of PDEM are given in this paper. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:449 / 458
页数:10
相关论文
共 50 条
  • [21] A method for the assessment of the optimal parameter of discrete-time switch model
    Razzaghi, R.
    Foti, C.
    Paolone, M.
    Rachidi, F.
    ELECTRIC POWER SYSTEMS RESEARCH, 2014, 115 : 80 - 86
  • [22] Parameter estimation in a generalized discrete-time model of density dependence
    Polansky, Leo
    de Valpine, Perry
    Lloyd-Smith, James O.
    Getz, Wayne M.
    THEORETICAL ECOLOGY, 2008, 1 (04) : 221 - 229
  • [23] Parameter Identification of Linear Discrete-Time Systems with Guaranteed Transient Performance
    Belov, Alexey A.
    Ortega, Romeo
    Bobtsov, Alexey A.
    IFAC PAPERSONLINE, 2018, 51 (15): : 1038 - 1043
  • [25] Parameter Identification Methods for Non-Linear Discrete-Time Systems
    Lehrer, Devon
    Adetola, Veronica
    Guay, Martin
    2010 AMERICAN CONTROL CONFERENCE, 2010, : 2170 - 2175
  • [26] New Algorithm for Identification of Discrete-Time Switched Linear Systems
    Lopes, Renato Vilela
    Borges, Geovany Araujo
    Ishihara, Joao Yoshiyuki
    2013 AMERICAN CONTROL CONFERENCE (ACC), 2013, : 6219 - 6224
  • [27] ALGORITHM FOR IDENTIFICATION OF MULTIVARIABLE DISCRETE-TIME LINEAR-SYSTEMS
    BRUCOLI, M
    MAIONE, B
    TORELLI, F
    ELECTRONICS LETTERS, 1978, 14 (10) : 313 - 315
  • [28] Nonlinear system identification using discrete-time neural networks with stable learning algorithm
    Korkobi, Talel
    Djemel, Mohamed
    Chtourou, Mohamed
    ICINCO 2008: PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL ICSO: INTELLIGENT CONTROL SYSTEMS AND OPTIMIZATION, 2008, : 351 - +
  • [29] Detection of Series DC Arc on a Distribution Node using Discrete-Time Parameter Identification Techniques
    Gajula, Kaushik K.
    Herrera, Luis
    Yao, Xiu
    THIRTY-FOURTH ANNUAL IEEE APPLIED POWER ELECTRONICS CONFERENCE AND EXPOSITION (APEC 2019), 2019, : 3007 - 3012
  • [30] Discrete-Time Neural Identification of a SIR Epidemic Model
    Covarrubias, Romeo
    Alanis, Alma Y.
    Rios, Daniel
    Sanchez, Edgar N.
    2018 IEEE LATIN AMERICAN CONFERENCE ON COMPUTATIONAL INTELLIGENCE (LA-CCI), 2018,