A Glowworm Swarm Optimization-Based Maximum Power Point Tracking for Photovoltaic/Thermal Systems under Non-Uniform Solar Irradiation and Temperature Distribution

被引:21
作者
Jin, Yi [1 ]
Hou, Wenhui [1 ]
Li, Guiqiang [2 ]
Chen, Xiao [3 ]
机构
[1] Univ Sci & Technol China, Dept Precis Machinery & Precis Instrumentat, 96 Jinzhai Rd, Hefei 230036, Peoples R China
[2] Univ Sci & Technol China, Dept Thermal Sci & Energy Engn, 96 Jinzhai Rd, Hefei 230026, Peoples R China
[3] Univ Sci & Technol China, State Key Lab Fire Sci, 96 Jinzhai Rd, Hefei 230026, Peoples R China
基金
美国国家科学基金会;
关键词
maximum power point tracking (MPPT); glowworm swarm optimization (GSO); photovoltaic-thermal (PV/T); non-uniform solar irradiation; temperature distribution; PV SYSTEMS; MPPT TECHNIQUE; CONTROLLER;
D O I
10.3390/en10040541
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
The output power of a photovoltaic (PV) system depends on the external solar irradiation and its own temperature. In order to obtain more power from the PV system, the maximum power point tracking (MPPT) is necessary. However, when the PV is partially shaded, there will be multiple peaks in the power-current (P-I) curve. The conventional MPPT methods may be invalid due to falling into the local peak. In addition, in a photovoltaic-thermal (PV/T) system, the non-uniform temperature distribution on PV will also occur, which complicates the situation. This paper presents a MPPT method with glowworm swarm optimization (GSO) for PV in a PV/T system under non-uniform solar irradiation and temperature distribution. In order to study the performance of the proposed method, the conventional methods including the perturbation and observe algorithm (P and O), and the fractional open-circuit voltage technique (FOCVT) are compared with it in this paper. Simulation results show that the proposed method can rapidly track the real maximum power point (MPP) under different conditions, such as the gradient temperature distribution, the fast variable solar irradiation and the variable partial shading. The outcome indicates the proposed method has obvious advantages, especially the performance being superior to the conventional methods under the partial shading condition.
引用
收藏
页数:13
相关论文
共 24 条
[11]   Theoretical and experimental analysis of genetic algorithms based MPPT for PV systems [J].
Hadji, Slimane ;
Gaubert, Jean-Paul ;
Krim, Fateh .
INTERNATIONAL CONFERENCE ON TECHNOLOGIES AND MATERIALS FOR RENEWABLE ENERGY, ENVIRONMENT AND SUSTAINABILITY -TMREES15, 2015, 74 :772-787
[12]   An Intelligent MPPT controller based on direct neural control for partially shaded PV system [J].
Kofinas, P. ;
Dounis, Anastasios I. ;
Papadakis, G. ;
Assimakopoulos, M. N. .
ENERGY AND BUILDINGS, 2015, 90 :51-64
[13]   Glowworm swarm optimization for simultaneous capture of multiple local optima of multimodal functions [J].
Krishnanand K.N. ;
Ghose D. .
Swarm Intelligence, 2009, 3 (2) :87-124
[14]   Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system [J].
Larbes, C. ;
Cheikh, S. M. Ait ;
Obeidi, T. ;
Zerguerras, A. .
RENEWABLE ENERGY, 2009, 34 (10) :2093-2100
[15]   Production of Polyhydroxyalkanoates (PHAs) by Bacillus Strain Isolated from Waste Water and Its Biochemical Characterization [J].
Mohapatra S. ;
Mohanta P.R. ;
Sarkar B. ;
Daware A. ;
Kumar C. ;
Samantaray D.P. .
Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, 2017, 87 (2) :459-466
[16]   Matlab/Simulink-Based Research on Maximum Power Point Tracking of Photovoltaic Generation [J].
Qin, Lijun ;
Lu, Xiao .
INTERNATIONAL CONFERENCE ON APPLIED PHYSICS AND INDUSTRIAL ENGINEERING 2012, PT A, 2012, 24 :10-18
[17]   A new MATLAB/Simulink model of triple-junction solar cell and MPPT based on artificial neural networks for photovoltaic energy systems [J].
Rezk, Hegazy ;
Hasaneen, El-Sayed .
AIN SHAMS ENGINEERING JOURNAL, 2015, 6 (03) :873-881
[18]   Renewable and sustainable energy reviews solar photovoltaic energy progress in India: A review [J].
Sahoo, Sarat Kumar .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2016, 59 :927-939
[19]   A PSO-based maximum power point tracking for photovoltaic systems under environmental and partially shaded conditions [J].
Sarvi, Mohammad ;
Ahmadi, Saeedeh ;
Abdi, Shirzad .
PROGRESS IN PHOTOVOLTAICS, 2015, 23 (02) :201-214
[20]   New variants of glowworm swarm optimization based on step size [J].
Singh A. ;
Deep K. .
International Journal of System Assurance Engineering and Management, 2015, 6 (03) :286-296