Novel mesh technique and its application in the wind field simulation for flexible spatial structure

Li, Lei; Zhou, Dai; Zhang, Xia-ping

doi:10.1007/s12204-010-1000-8

Cited by 4 publications

(6 citation statements)

References 9 publications

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“…ω 1 , ω 2 , ω 3 and ω 4 are the weight coefficients of the four variables respectively, which are proportional to the correlation coefficient between the corresponding feature and the PV output, and the sum is 1 [19].…”

Section: Clustering Resultsmentioning

confidence: 99%

“…For each weather type, among them, µ SCF is not fixed and can be appropriately adjusted based on actual data [19].…”

Section: Clustering Resultsmentioning

confidence: 99%

“…These clustering techniques ignore the multiple impacts of meteorological elements on PV output and employ partial meteorological parameters as classification indices without considering the coupling relationships among distinct meteorological components. Key impacting elements are identified and analyzed using the Pearson correlation coefficient in [19]. These components are then weighted and added together to produce clustering indices.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Model for Ultra-short-term PV Prediction Using SOM Clustering and ECA

Zhu,

Wang,

Zhang

et al. 2024

Preprint

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For the grid to operate safely and steadily and for PV electricity to be connected on a broad scale, the precision of the ultra-short-term PV power prediction is crucial. A combination model of ultra-short-term PV prediction based on an attention mechanism is proposed to increase the prediction accuracy of PV output power under various weather circumstances. First, using a Pearson correlation coefficient analysis, important climatic variables that are closely associated with PV power generation are selected and normalized on a monthly basis. The Sky Condition Factor (SCF), a classification index, is then obtained by computing a weighted summation. This reduces the dimensionality of the input variables and eliminates seasonal influence on weather classification and the coupling interactions among various meteorological elements. Second, an unsupervised clustering of SCFs using a Self-Organizing Map (SOM) neural network is used to classify three types of weather. After that, CNN prediction models are built for each of the three types of weather. The Efficient Channel Attention (ECA) module is then added, allowing the model to focus on key feature information and increase prediction accuracy by adaptively assigning phase weights to each of the multiple channels of feature information that the CNN has extracted. Lastly, the efficacy of the suggested prediction model is verified by simulations run on historical observed data, which demonstrate an improvement in the prediction model's accuracy under various weather conditions when compared to the model without the ECA module.

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Section: Clustering Resultsmentioning

confidence: 99%

“…For each weather type, among them, µ SCF is not fixed and can be appropriately adjusted based on actual data [19].…”

Section: Clustering Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Hybrid Model for Ultra-short-term PV Prediction Using SOM Clustering and ECA

Zhu,

Wang,

Zhang

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…In the past 20 years, safety assessment has been gradually applied in structural engineering, chemical disasters, information security, and other fields, while there have been relatively few safety assessment theories for cranes [16][17][18]. The load of the crane is usually large, ranging from several tons to thousands of tons, and the lifting height ranges from tens of meters to hundreds of meters [19].…”

Section: Introductionmentioning

confidence: 99%

Prediction and Optimization Algorithm for Intersection Point of Spatial Multi-Lines Based on Photogrammetry

Zhao

Hao

Zhao

et al. 2022

Sensors

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The basic theory of photogrammetry is mature and widely used in engineering. The environment in engineering is very complex, resulting in the corners or multi-line intersections being blocked and unable to be measured directly. In order to solve this problem, a prediction and optimization algorithm for intersection point of spatial multi-lines based on photogrammetry is proposed. The coordinates of points on space lines are calculated by photogrammetry algorithm. Due to the influence of image point distortion and point selection error, many lines do not strictly intersect at one point. The equations of many space lines are used to fit their initial value of intersection point. The initial intersection point is projected onto each image, and the distances between the projection point and each line on the image plane are used to weight the calculated spatial lines in combination with the information entropy. Then the intersection point coordinates are re-fitted, and the intersection point is repeatedly projected and recalculate until the error is less than the threshold value or reached the set number of iterations. Three different scenarios are selected for experiments. The experimental results show that the proposed algorithm significantly improves the prediction accuracy of the intersection point.

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“…Zhou Li and Xi Guang studied the numerical and analysis of wind speed distribution under high-rise building using CFD software. There group also puts forward pressure model to discuss the influence of the wind load on the building [1]. Zhu Y and Lin B studied the simulation of urban street convection wind flow structure and turbulence character [2].…”

Section: Introductionmentioning

confidence: 99%

Simulation of Wind Speed in Campus Based on FLUENT

Chao

Xiao

2013

AMR

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In order to study urban surface dust distribution, a three-dimensional model is proposed and the distribution of wind and the distribution law of air pollutants are researched. 3D campus of Shanghai University as a typical area is selected. The standard height (Twenty two meters) of teaching building for reference has been chosen. In different distances such as Eight、Twelve、Fifteen、Twenty meters, the amount and distribution of wind speed were obtained from simulation using FLUENT software. Combined with the particulate of air pollution’s distribution in urban surface, the optimized design of the main campus’s building spacing is analyzed. The results show that when the building space is about Fifteen meters, the concentration of pollutants and the distribution of wind speed is optimized.

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Novel mesh technique and its application in the wind field simulation for flexible spatial structure

Cited by 4 publications

References 9 publications

A Hybrid Model for Ultra-short-term PV Prediction Using SOM Clustering and ECA

A Hybrid Model for Ultra-short-term PV Prediction Using SOM Clustering and ECA

Prediction and Optimization Algorithm for Intersection Point of Spatial Multi-Lines Based on Photogrammetry

Simulation of Wind Speed in Campus Based on FLUENT

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