scholarly journals An Approach for Estimating Solar Photovoltaic Potential Based on Rooftop Retrieval from Remote Sensing Images

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3172 ◽  
Author(s):  
Xiaoyang Song ◽  
Yaohuan Huang ◽  
Chuanpeng Zhao ◽  
Yuxin Liu ◽  
Yanguo Lu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Solar Radiation ◽  
Solar Energy ◽  
Image Data ◽  
Surface Model ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Remote Sensing Images ◽  
Time Step ◽  
Pv Systems

Solar energy is the most clean renewable energy source and has good prospects for future sustainable development. Installation of solar photovoltaic (PV) systems on building rooftops has been the most widely applied method for using solar energy resources. In this study, we developed an approach to simulate the monthly and annual solar radiation on rooftops at an hourly time step to estimate the solar PV potential, based on rooftop feature retrieval from remote sensing images. The rooftop features included 2D rooftop outlines and 3D rooftop parameters retrieved from high-resolution remote sensing image data (obtained from Google Maps) and digital surface model (DSM, generated from the Pleiades satellite), respectively. We developed the building features calculation method for five rooftop types: flat rooftops, shed rooftops, hipped rooftops, gable rooftops and mansard rooftops. The parameters of the PV modules derived from the building features were then combined with solar radiation data to evaluate solar photovoltaic potential. The proposed method was applied in the Chao Yang District of Beijing, China. The results were that the number of rooftops available for PV systems was 743, the available rooftop area was 678,805 m2, and the annual PV electricity potential was 63.78 GWh/year in the study area, which has great solar PV potential. The method to perform precise calculation of specific rooftop solar PV potential developed in this study will guide the formulation of energy policy for solar PV in the future.

scholarly journals Evaluating the Impacts of Ground and Atmospheric Conditions on the Efficiency of Solar Energy System and Its Economic Analysis

2018 ◽  
Author(s):  
Ali Saleh Aziz ◽  
Mohammad Faridun Naim Tajuddin ◽  
Sanjeevikumar Padmanaban ◽  
Lucian Mihet-Popa ◽  
Mohd Rafi Adzman ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Ambient Temperature ◽  
Economic Performance ◽  
Base Station ◽  
Base Case ◽  
Solar Pv ◽  
Pv Systems ◽  
Pv Array ◽  
Pv Modules

The There are many factors influencing the performance of photovoltaic (PV) systems. Among these factors, temperature and solar radiation are two major parameters that have a large effect on the efficiency of PV systems. The cell temperature of PV panels is related to the ambient temperature while the solar radiation incident on the surface of the PV modules depends on the slope and azimuth of these modules. Furthermore, ground reflectance (albedo) affects the irradiance incident on the PV panel surface, which in turn affects the output of a PV system. Nevertheless, the effects of these factors on the economic performance of the solar PV systems are scarcely reported. This paper presents a complete design of a stand-alone PV/battery system to supply electric power for a mobile base station in Choman, Erbil, Iraq. The effects of different factors on the total electricity produced by PV arrays and its economic performance are simultaneously investigated. HOMER software has been used as a tool for the techno-economic and environmental analysis. As indicated from the simulation results, the PV array capacity and its economic performance are highly affected by the variation of the slope and azimuth. With a base case (albedo of 20% and average annual ambient temperature of 11°C), the best feasible system which is achieved by facing PV due to south with a tilt angle of 40° or 45°, is found to have net present cost (NPC) of 70595 $ and cost of energy (COE) of 0.54 $/kWh. Moreover, the results indicate that increasing the ground reflectance from 10% to 90% results in a 7.2% decrease in the PV array capacity and about 3% decrease in the NPC and COE. On the other hand, increasing the ambient temperature from 0°C to 40°C results in a 19.7% increase in the PV array capacity and an 8.2% increase in the NPC and COE. Furthermore, according to the ambient temperature of Choman, using PV modules with high sensitivity to temperature is found to be an attractive option. Provided simulation performance analysis proves that the studied parameters must be treated well to establish an enabling environment for solar energy development in Iraq.

scholarly journals Effect of Temperature on Solar Photovoltaic Panel Efficiency

2019 ◽  
Vol 8 (6) ◽  
pp. 2593-2595
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Heat Energy ◽  
Effect Of Temperature ◽  
Solar Photovoltaic ◽  
Environmental Condition ◽  
Solar Pv ◽  
Photovoltaic Panel ◽  
Pv Panel ◽  
Photovoltaic Solar Cells

Solar energy is the important energy source for future. Lot of devices are used for capture the energy from solar radiation and convert into useful form of energy. Solar PV (Photovoltaic) Panels are the promising devices convert the solar radiation into electrical form of energy. The partial portion of solar energy may be converted into electricity remaining in the form heat energy. Solar PV panel performance varies with temperature increase. The PV panel temperature has effect on power and voltage. Due to increase of temperature, the photovoltaic solar cells efficiency may be decreased. The life of the panel also will be decreased. In this paper how the heat energy received from solar radiation in the form of temperature affect the solar panel efficiency was analysed by experiment conducted with solar PV panel of 50W in the real outdoor environmental condition.

scholarly journals A Public Dataset for Fine-Grained Ship Classification in Optical Remote Sensing Images

2021 ◽  
Vol 13 (4) ◽  
pp. 747
Author(s):  
Yanghua Di ◽  
Zhiguo Jiang ◽  
Haopeng Zhang
Keyword(s):  
Remote Sensing ◽  
Image Data ◽  
Remote Sensing Image ◽  
Google Earth ◽  
Optical Remote Sensing ◽  
Remote Sensing Images ◽  
Visual Categorization ◽  
Class Differences ◽  
Fine Grained ◽  
Ship Classification

Fine-grained visual categorization (FGVC) is an important and challenging problem due to large intra-class differences and small inter-class differences caused by deformation, illumination, angles, etc. Although major advances have been achieved in natural images in the past few years due to the release of popular datasets such as the CUB-200-2011, Stanford Cars and Aircraft datasets, fine-grained ship classification in remote sensing images has been rarely studied because of relative scarcity of publicly available datasets. In this paper, we investigate a large amount of remote sensing image data of sea ships and determine most common 42 categories for fine-grained visual categorization. Based our previous DSCR dataset, a dataset for ship classification in remote sensing images, we collect more remote sensing images containing warships and civilian ships of various scales from Google Earth and other popular remote sensing image datasets including DOTA, HRSC2016, NWPU VHR-10, We call our dataset FGSCR-42, meaning a dataset for Fine-Grained Ship Classification in Remote sensing images with 42 categories. The whole dataset of FGSCR-42 contains 9320 images of most common types of ships. We evaluate popular object classification algorithms and fine-grained visual categorization algorithms to build a benchmark. Our FGSCR-42 dataset is publicly available at our webpages.

Grid Parity of Residential Building Rooftop Solar PV in India

2021 ◽  
pp. 19-40
Author(s):  
Rakesh Dalal ◽  
Kamal Bansal ◽  
Sapan Thapar
Keyword(s):  
Residential Building ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Indian Government ◽  
Pv System ◽  
Pv Systems ◽  
Grid Parity ◽  
Solar Pv System ◽  
Utility Grid ◽  
Rooftop Solar

Rooftop solar photovoltaic(PV) installation in India have increased in last decade because of the flat 40 percent subsidy extended for rooftop solar PV systems (3 kWp and below) by the Indian government under the solar rooftop scheme. From the residential building owner's perspective, solar PV is competitive when it can produce electricity at a cost less than or equal grid electricity price, a condition referred as “grid parity”. For assessing grid parity of 3 kWp and 2 kWp residential solar PV system, 15 states capital and 19 major cities were considered  for the RET screen simulation by using solar isolation, utility grid tariff, system cost and other economic parameters. 3 kWp and 2 kWp rooftop solar PV with and without subsidy scenarios were considered for simulation using RETscreen software. We estimate that without subsidy no state could achieve grid parity for 2kWp rooftop solar PV plant. However with 3 kWp rooftop solar PV plant only 5 states could achieve grid parity without subsidy and with government subsidy number of states increased to 7, yet wide spread parity for residential rooftop solar PV is still not achieved. We find that high installation costs, subsidized utility grid supply to low energy consumer and financing rates are major barriers to grid parity.

Unsupervised labelling of remote sensing images based on force field clustering

2021 ◽  
pp. 1-14
Author(s):  
Zhenggang Wang ◽  
Jin Jin
Keyword(s):  
Remote Sensing ◽  
Force Field ◽  
Image Data ◽  
Model Parameters ◽  
Remote Sensing Images ◽  
Initial Cluster ◽  
Data Points ◽  
Global Optimal ◽  
Density Force

Remote sensing image segmentation provides technical support for decision making in many areas of environmental resource management. But, the quality of the remote sensing images obtained from different channels can vary considerably, and manually labeling a mass amount of image data is too expensive and Inefficiently. In this paper, we propose a point density force field clustering (PDFC) process. According to the spectral information from different ground objects, remote sensing superpixel points are divided into core and edge data points. The differences in the densities of core data points are used to form the local peak. The center of the initial cluster can be determined by the weighted density and position of the local peak. An iterative nebular clustering process is used to obtain the result, and a proposed new objective function is used to optimize the model parameters automatically to obtain the global optimal clustering solution. The proposed algorithm can cluster the area of different ground objects in remote sensing images automatically, and these categories are then labeled by humans simply.

Preliminary results on the determination of solar energy potential using LiDAR technology

2015 ◽  
Vol 6 (1) ◽  
pp. 11-17 ◽  
Author(s):  
G. Szabó ◽  
P. Enyedi ◽  
Gy. Szabó ◽  
I. Fazekas ◽  
T. Buday ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Energy Production ◽  
Alternative Energy ◽  
Surface Model ◽  
Solar Panels ◽  
Energy Potential ◽  
Potential Surfaces ◽  
Large Power ◽  
Automatic Data

According to the challenge of the reduction of greenhouse gases, the structure of energy production should be revised and the increase of the ratio of alternative energy sources can be a possible solution. Redistribution of the energy production to the private houses is an alternative of large power stations at least in a partial manner. Especially, the utilization of solar energy represents a real possibility to exploit the natural resources in a sustainable way. In this study we attempted to survey the roofs of the buildings with an automatic method as the potential surfaces of placing solar panels. A LiDAR survey was carried out with 12 points/m2 density as the most up-to-date method of surveys and automatic data collection techniques. Our primary goal was to extract the buildings with special regard to the roofs in a 1 km2 study area, in Debrecen. The 3D point cloud generated by the LiDAR was processed with MicroStation TerraScan software, using semi-automatic algorithms. Slopes, aspects and annual solar radiation income of roof planes were determined in ArcGIS10 environment from the digital surface model. Results showed that, generally, the outcome can be regarded as a roof cadaster of the buildings with correct geometry. Calculated solar radiation values revealed those roof planes where the investment for photovoltaic solar panels can be feasible.

scholarly journals U-net Network for Building Information Extraction of Remote-Sensing Imagery

2018 ◽  
Vol 14 (12) ◽  
pp. 179
Author(s):  
Jingtan Li ◽  
Maolin Xu ◽  
Hongling Xiu
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Information Extraction ◽  
Image Data ◽  
Semantic Segmentation ◽  
Remote Sensing Image ◽  
Remote Sensing Images ◽  
Training Set ◽  
Building Information ◽  
The Face

With the resolution of remote sensing images is getting higher and higher, high-resolution remote sensing images are widely used in many areas. Among them, image information extraction is one of the basic applications of remote sensing images. In the face of massive high-resolution remote sensing image data, the traditional method of target recognition is difficult to cope with. Therefore, this paper proposes a remote sensing image extraction based on U-net network. Firstly, the U-net semantic segmentation network is used to train the training set, and the validation set is used to verify the training set at the same time, and finally the test set is used for testing. The experimental results show that U-net can be applied to the extraction of buildings.

scholarly journals Shared Solar and Battery Storage Configuration Effectiveness for Reducing the Grid Reliance of Apartment Complexes

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4820 ◽  
Author(s):  
Moiz Masood Syed ◽  
Gregory M. Morrison ◽  
James Darbyshire
Keyword(s):  
Residential Buildings ◽  
Primary Objective ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Battery Storage ◽  
Pv Systems ◽  
Apartment Buildings ◽  
Self Sufficiency ◽  
Research Gap ◽  
Apartment Complexes

More than 2 million houses in Australia have installed solar photovoltaic (PV) systems; however, apartment buildings have adopted a low percentage of solar PV and battery storage installations. Given that grid usage reduction through PV and battery storage is a primary objective in most residential buildings, apartments have not yet fully benefited from installations of such systems. This research presents shared microgrid configurations for three apartment buildings with PV and battery storage and evaluates the reduction in grid electricity usage by analyzing self-sufficiency. The results reveal that the three studied sites at White Gum Valley achieved an overall self-sufficiency of more than 60%. Owing to the infancy of the shared solar and battery storage market for apartment complexes and lack of available data, this study fills the research gap by presenting preliminary quantitative findings from implementation in apartment buildings.

scholarly journals A Study on Coastline Extraction and Its Trend Based on Remote Sensing Image Data Mining

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Yun Zhang ◽  
Xueming Li ◽  
Jianli Zhang ◽  
Derui Song
Keyword(s):  
Remote Sensing ◽  
Data Mining ◽  
Prediction Method ◽  
Image Data ◽  
Chromatic Aberration ◽  
Grey Prediction ◽  
Remote Sensing Images ◽  
Canny Operator ◽  
Matching Algorithm ◽  
Edge Detection Method

In this paper, data mining theory is applied to carry out the field of the pretreatment of remote sensing images. These results show that it is an effective method for carrying out the pretreatment of low-precision remote sensing images by multisource image matching algorithm with SIFT operator, geometric correction on satellite images at scarce control points, and other techniques; the result of the coastline extracted by the edge detection method based on a chromatic aberration Canny operator has a height coincident with the actual measured result; we found that the coastline length of China is predicted to increase in the future by using the grey prediction method, with the total length reaching up to 19,471,983 m by 2015.

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