Open AccessControl strategy of grid-connected inverter droop based on GMPPT method
Author(s) -
Xuyang Zhang,
Jun Teng,
PengQiao Zhang,
Minglei Jia,
Cong Yu,
Yifei Sun,
Jia Sun,
Pengran Ma,
Bowen Zhou,
Nanjun Cao,
Hengyu Liu,
Zhensheng Yu
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/467/1/012115
Subject(s) - maximum power point tracking , control theory (sociology) , voltage droop , computer science , photovoltaic system , inverter , grid , matlab , particle swarm optimization , voltage , engineering , control (management) , voltage source , electrical engineering , mathematics , algorithm , geometry , artificial intelligence , operating system
The conductance increment method (INC) can be quickly and accurately stabilized at the maximum power point (MPP) but easily falls into the local extreme point (LMPP) in the shadow environment. Considering the particle swarm optimization (PSO) can quickly achieve global optimal search but the number of iterations is too large when local convergence, leading to fluctuation and energy loss. Therefore, a global maximum power point tracking (GMPPT) is proposed, which combined the PSO and INC and improved them. In this paper, the research object is the single-phase two-stage PV grid-connected system. The GMPPT needs a stable DC voltage (U dc ) to track accurately and the grid-connected inverter needs a stable U dc in order to ensure the quality of grid power. Therefore, the goal of the inverter control is to achieve the combination of GMPPT and grid-connected control. Based on the characteristics of PV power generation, a PV grid-connected droop control strategy based on GMPPT is proposed, which realizes the stability of Udc and the output of MPP and meets grid-connected requirements. Finally, the simulation model of PV grid-connected system based on Matlab/Simulink software is used to verify the effectiveness of the proposed control strategy.