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A Review of MPPT Algorithms for Partial Shading Conditions

100%
Erdem Z.
Acta Physica Polonica A
|
2017
|
vol. 132
|
issue 3
1128-1133
EN
Maximum power point tracker in a photovoltaic system allows to maximize the energy drawn from the connected photovoltaic modules. In the partial shade conditions there can be more than one maximum point in photovoltaic output power curve. The solution for this situation is a maximum power point tracker algorithm, which finds the global maximum. In literature, there is a large number of studies on maximum power point trackers. Therefore designers are drowning in a sea of knowledge. This study eliminates similar studies and classified them into groups, and at the end of the study a comparison table is given to guide the designers in the performance information of the selected studies. This study aims to guide the designers to make a sensible selection of a maximum power point tracker algorithm for partial shade conditions.
2
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An Advanced Particle Swarm Optimization Algorithm for MPPTs in PV Systems

100%
Erdem Z.
Acta Physica Polonica A
|
2017
|
vol. 132
|
issue 3
1134-1139
EN
Maximum power point trackers are in charge of absorbing the maximum potential power from the photovoltaic panels. Thus, this makes the maximum power point trackers the fundamental parts of the photovoltaic panel systems. The conventional maximum power point tracker algorithms are working well under balanced insolation conditions, however when the partial shade condition occurs, those algorithms are trapped at the local maxima. Hence, under partial shade conditions, the need for a global maximum power point tracking algorithm arises. Particle swarm optimization is a preferential algorithm of maximum power point trackers in literature, especially in partial shade conditions. This paper is focused on improving the existing particle swarm optimization algorithm for maximum power point trackers. The proposed advanced particle swarm optimization algorithm aims to catch the global maximum power point much faster, accurately and to reduce the chatter in the power curve. The proposed method accelerates the global maximum tracking time with gridding the initial search area. The effectiveness of the proposed method is demonstrated with simulation results and these results are compared with a conventional particle swarm optimization method under step changes in irradiance and partial shade conditions of an array of photovoltaic panels.
3
Content available remote

Path Planning for Multiple Mobile Robots Using A* Algorithm

68%
Batik Garip Z., Karayel D., Ozkan S., Atali G.
Acta Physica Polonica A
|
2017
|
vol. 132
|
issue 3
685-688
EN
One of the main problems in path planning for multiple mobile robots is to find the optimal path between two points so that robots can follow the shortest path and consume the least energy. Also, motion planning is important to avoid collisions if multiple mobile robots are running together within environments with obstacles. In this study, motion planning for multiple robots has been proposed. It is desired that robots could move in coordination with each other from the starting point to the destination point on a plane. The coordinates of the objects and mobile robots have been acquired using image processing with a single ceiling camera. The path planning for the shortest distance has been performed using A* algorithm in dynamic frame between robot-object and object-target point, respectively. A graphical user interface has been developed based on MATLAB GUI. It is hoped that the developed system will have a wide area of applications in industry and will make important contributions for the improvement of manufacturing, assembly, transportation and storage technologies.
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