A Simulated Annealing Global Maximum Power Point Tracking Approach for PV Modules Under Partial Shading Conditions

Lyden, Sarah; Haque, M. E.

doi:10.1109/tpel.2015.2468592

Cited by 216 publications

(111 citation statements)

References 49 publications

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“…Within the meta-heuristic algorithms, particle swarm optimization (PSO) is the most used algorithm in literature, thanks to its simple implementation and powerful behaviour at PSC. Other methods in this group are, simulated annealing [8], Grey-Wolf optimization [9], DEPSO [10], firefly colony [11] and artificial bee colony. All these algorithms are investigated for advantages and drawbacks in the following sub-sections.…”

Section: Meta-heuristicsmentioning

confidence: 99%

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A Review of MPPT Algorithms for Partial Shading Conditions

Erdem

2017

Acta Phys. Pol. A

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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.

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Section: Meta-heuristicsmentioning

confidence: 99%

“…Paper [8] proposes a simulated annealing-based (SA) global maximum power point tracking technique designed for PSC. The SA method is based on following the heating and cooling processes in metals to find the global optimum solution.…”

Section: Meta-heuristicsmentioning

confidence: 99%

A Review of MPPT Algorithms for Partial Shading Conditions

Erdem

2017

Acta Phys. Pol. A

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“…Merge Task is a timed merging program that dynamically changes the merging operation interval based on the file flow rate into the Files Container to ensure that there are enough samples to achieve the optimal merging. The optimal merging here means that the size of the final merged file is closest to the value of the memory block (default 64M), which is implemented by the simulated annealing algorithm [13]. The client merges the small files into large files marked with TaskId and records the merge order in memory.…”

Section: The Client's Operationsmentioning

confidence: 99%

Exploiting FastDFS Client-based Small File Merging

Chen¹,

Zhang²

2016

Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

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Abstract. How to store masses of small files is a generally acknowledged problem in industry and academia. Small file merging is the most successful strategy to solve this problem, which has been supported by many distributed filesystems, such as FastDFS. However, in FastDFS, our experiments indicate that excessively wide striping causes performance degradation, and pre-allocated space causes data loss or error. Therefore, this paper presents a client-based small file merging scheme based on the characteristics of online web application. This scheme makes full use of the resources of the web server and optimizes the small file merging with the annealing algorithm to improve the throughput. Experimental results show that the write performance are improved by 52.03% and query performance by 27.69% compared with the original FastDFS small file merging scheme.

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“…The redundant representation is adopted by the NSCT filter, which can effectively capture image characteristics, and distinguish between noise and image edge [9]. Thus, it has a very good denoising effect.…”

Section: 1、nsct Filtermentioning

confidence: 99%

“…2) The simulated annealing algorithm is a kind of intelligent data optimization algorithm [9], which is used to filter the real part spectrum data. Two minimum amplitudes 1 The fuzzy length d and the fuzzy angle θ are known.…”

Section: 2、 Spectrum Characteristics-based Fuzzy Regression Model Cmentioning

confidence: 99%

Small Celestial Body Image Restoration Based on Spectrum Characteristics

Tao¹,

Kang²,

Liu³

2016

Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications

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Abstract.To remove the blur of the image from optical navigation camera, a image restoration method based on spectrum characteristics is proposed. In this method, image denoising pretrea tment is first implemented by the NSCT filter. Then, to obtain the minimum amplitude distanc e, the paper optimizes the image spectrum characteristic by using the simulated annealing al gorithm. And then the minimum amplitude distance can be obtained. There the point spread fu nction is established. Finally, blurred image is recovered by the Lucy -Richardson algorithm.T he recovery quality is evaluated by the Laplace gradient and the average gray level gradient. T he simulation results demonstrate that the proposed method in the paper improves the quality of the restored small celestial body image, and the visual effect is also very ideal. 1、IntroductionIn the process of the deep space exploration, the imaging system of the optical optical camera is vulnerable to the flight speed and the cosmic rays [1], which cause the image fuzzy and inconvenience for image information analysis. Thus, how to restore fuzzy image is a difficulty of image information process in the deep space exploration.The image restoration of small celestial body mainly consists of the image denoising pretreatment and the image degradation process estimation. At present, there are many relevant researches about the image denoising pretreatment. For instance, the median filtering algorithm has a very good effect on the salt and pepper noise, but it is not ideal to other interference noises [1]. The bilateral filter algorithm can eliminate the image noise, while it cannot make image detail intact [2]. The degradation function is important to determine the degradation process. The degradation function of the optical camera is the point-spread function (PSF) [3]. For the point-spread function, a lot of researches have been done by domestic and foreign scholars. X. H. Wang et al, considered that the distance between the spectrum center and the adjacent black belt is inversely proportional to the blurred length [4]. But it is only a project of the degradation function estimation, and does not have a specific quantitative formula. N. Norouzi et al., put forward a method of derivative, which can detect image blurred length. However, the error is very serious under the condition of noise [5].For the image blur problem caused by the optical camera, this paper proposes the NSC algorithm, which mainly includes image denoising pretreatment based on the NSCT filter and fuzzy regression model construction based on the spectrum characteristics. 2、NSC algorithm 2.1、NSCT filterThe non -subsampled contourlet (NSCT) filter is composed of the non -subsampled pyramid (NSP) [6] and the non -subsampled direction filter group (NSDFB) [7]. The redundant representation is adopted by the NSCT filter, which can effectively capture image characteristics, and distinguish between noise and image edge [9]. Thus, it has a very good denoising effect.The non-subsampled pyramid (NSP) is used for ...

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A Simulated Annealing Global Maximum Power Point Tracking Approach for PV Modules Under Partial Shading Conditions

Cited by 216 publications

References 49 publications

A Review of MPPT Algorithms for Partial Shading Conditions

A Review of MPPT Algorithms for Partial Shading Conditions

Exploiting FastDFS Client-based Small File Merging

Small Celestial Body Image Restoration Based on Spectrum Characteristics

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