Open AccessMaximum power point tracking scheme with partial shading detection for two‐stage grid‐connected photovoltaic inverters
Author(s) -
Huang Lei,
Zhang Jiyuan,
Cui Qiong,
Wang Hao,
Shu Jie
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.8547
Subject(s) - photovoltaic system , maximum power point tracking , maximum power principle , matlab , computer science , voltage , power (physics) , maxima and minima , process (computing) , control theory (sociology) , grid , shading , mathematics , engineering , electrical engineering , inverter , physics , artificial intelligence , mathematical analysis , geometry , control (management) , computer graphics (images) , quantum mechanics , operating system
This paper proposes a maximum power point tracking (MPPT) method with partial shading (PS) detection based on modified PI incremental conductance (IC) for photovoltaic inverters. To accurately trigger the algorithm, a PS detecting approach based on voltage deviation is derived through the comparison of voltage and current characteristics under uniform and non‐uniform insolation. To track the global maximum power point (GMPP) precisely and fast, a global search scheme considering appropriate voltage reference, search direction and termination criteria is presented. The modified PI‐based IC method is implemented in the local search process. In order to verify the effectiveness of the algorithm, the proposed method is utilised in the two‐stage grid‐connected photovoltaic inverters built in MATLAB/Simulink. The performance of the scheme is compared with the traditional IC method under step‐changing and gradual‐changing insolation and various temperature. In all simulation cases, the proposed approach can identify the PS with multiple local maxima, accurately trigger the global search process and track the GMPP. The search periods are around 0.1–0.2 s, and the efficiencies of PV generation under steady state are normally above 99.5%. The presented method can improve the efficiency of distributed and centralised PV system.