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 Comparative Efficiency Assessment of MPPT Algorithms in Photovoltaic Systems
Tác giả hoặc Nhóm tác giả: Hong Viet Phuong Nguyen, Thanh Tung Huynh, Van Tan Nguyen
Nơi đăng: International Journal of Renewable Energy Research; Số: 4;Từ->đến trang: 2061-2067;Năm: 2022
Lĩnh vực: Kỹ thuật; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
Algorithms of maximum power point tracking are widely used in most of photovoltaic systems to optimize the output power which depends on ambient conditions such as solar irradiance and PV arrays’ temperature. In general, these techniques can be classified into two categories: conventional algorithms including Perturb and Observe (P&O) and Incremental Conductance (INC), and artificial intelligence algorithms including Artificial Neural Network (ANN). In this investigation, a survey of these algorithms is conducted to analyze, compare and assess their performances when they are integrated in a PV power system under dynamic changed conditions. The simulation results obtained from MATLAB/Simulink environment show that the dynamic performances of intelligent MPPT controller are much better than those of P&O and INC algorithms.
ABSTRACT
Algorithms of maximum power point tracking are widely used in most of photovoltaic systems to optimize the output power which depends on ambient conditions such as solar irradiance and PV arrays’ temperature. In general, these techniques can be classified into two categories: conventional algorithms including Perturb and Observe (P&O) and Incremental Conductance (INC), and artificial intelligence algorithms including Artificial Neural Network (ANN). In this investigation, a survey of these algorithms is conducted to analyze, compare and assess their performances when they are integrated in a PV power system under dynamic changed conditions. The simulation results obtained from MATLAB/Simulink environment show that the dynamic performances of intelligent MPPT controller are much better than those of P&O and INC algorithms.
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