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Performance of smart maximum power point tracker under partial shading conditions of photovoltaic systems
Partial shading on photovoltaic (PV) modules reduces the generated power of the PV system than the maximum power generated from each module separately. The shaded PV module acts as a load to unshaded ones which can lead to hot-spot. To alleviate the effect of partial shading, bypass diodes should be connected across each PV modules. Connecting several PV modules together produces multiple peaks (one global peak (GP) and multiple local peaks (LPs)) on partial shading conditions. Maximum power point tracker conventional techniques are designed to follow the GP but they stuck around LPs such as fuzzy logic controller (FLC). In this paper, modified particle swarm optimization (MPSO) using genetic algorism has been used to follow the GP under any operating conditions. MPSO has been studied and compared with the FLC technique to show the superiority of this technique under all operating conditions. Co-simulation between Matlab/Simulink and PSIM has been used to model the PV system under partial shading conditions. The simulation results show that the MPSO technique is more effective than FLC in following the GP. The generated power increases considerably with the MPSO than the FLC technique in shading conditions.
Performance of smart maximum power point tracker under partial shading conditions of photovoltaic systems
Partial shading on photovoltaic (PV) modules reduces the generated power of the PV system than the maximum power generated from each module separately. The shaded PV module acts as a load to unshaded ones which can lead to hot-spot. To alleviate the effect of partial shading, bypass diodes should be connected across each PV modules. Connecting several PV modules together produces multiple peaks (one global peak (GP) and multiple local peaks (LPs)) on partial shading conditions. Maximum power point tracker conventional techniques are designed to follow the GP but they stuck around LPs such as fuzzy logic controller (FLC). In this paper, modified particle swarm optimization (MPSO) using genetic algorism has been used to follow the GP under any operating conditions. MPSO has been studied and compared with the FLC technique to show the superiority of this technique under all operating conditions. Co-simulation between Matlab/Simulink and PSIM has been used to model the PV system under partial shading conditions. The simulation results show that the MPSO technique is more effective than FLC in following the GP. The generated power increases considerably with the MPSO than the FLC technique in shading conditions.
Performance of smart maximum power point tracker under partial shading conditions of photovoltaic systems
Eltamaly, Ali. M. (Autor:in)
01.07.2015
16 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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| British Library Online Contents | 2017
| British Library Online Contents | 2017