2022 6th International Conference on Green Energy and Applications (ICGEA)最新文献_第5页

Environmental and Power Quality Assessment of Railway Traction Power Substations 铁路牵引变电站环境与电能质量评价

2022 6th International Conference on Green Energy and Applications (ICGEA) Pub Date : 2022-03-04 DOI: 10.1109/icgea54406.2022.9792029

M. De Santis, L. Silvestri, Luca Vallotto, G. Bella

引用次数: 0

The Multi-Actor Multi-Criteria Analysis (MAMCA) as a Tool to Evaluate Shaanxi Renewable Energy Projects 基于多主体多标准分析的陕西可再生能源项目评价方法

2022 6th International Conference on Green Energy and Applications (ICGEA) Pub Date : 2022-03-04 DOI: 10.1109/icgea54406.2022.9791886

Hui Li, Xin Zan, Jiahao Tu

引用次数: 0

Automatic on Field Detection and Localization of Defective Solar Photovoltaic Modules from Orthorectified RGB UAV Imagery 基于正校正RGB无人机图像的太阳能光伏组件缺陷自动现场检测与定位

2022 6th International Conference on Green Energy and Applications (ICGEA) Pub Date : 2022-03-04 DOI: 10.1109/icgea54406.2022.9791946

Hafsa Elidrissi, Hafsa Achakir, Yahya Zefri, I. Sebari, G. Aniba, H. Hajji

{"title":"Automatic on Field Detection and Localization of Defective Solar Photovoltaic Modules from Orthorectified RGB UAV Imagery","authors":"Hafsa Elidrissi, Hafsa Achakir, Yahya Zefri, I. Sebari, G. Aniba, H. Hajji","doi":"10.1109/icgea54406.2022.9791946","DOIUrl":"https://doi.org/10.1109/icgea54406.2022.9791946","url":null,"abstract":"In the maintenance framework of solar photovoltaic (PV) installations, modules’ defect detection, identification and on field localization play a key role in preserving the reliability and efficiency of the electrical power generation. Remotely sensed imagery by means of Unmanned Aerial Vehicles (UAVs) is actively used in this context as it allows faster, cost-effective and contactless characterization of modules’ surface together with large-scale deployment. We develop herein an end-to-end approach to detect, identify and locate on field defects on PV installations based on RGB imagery acquired by UAVs. The approach is fundamentally designed for large-scale applications and comprises: (1) A photogrammetric image acquisition and post-processing phase that produces one orthorectified and georeferenced support covering the entire inspected site; (2) A module extraction phase that yields the individual images of modules; and (3) A deep learning-based defect detection stage using a fine-tuned instance of the YOLOv4 architecture. The approach was developed, validated and tested using a dataset collected from two large-scale PV sites comprising 35 305 modules. The developed defect detector scored a mean Average Precision (mAP) of 83% and 73% respectively on the validation and test sets.","PeriodicalId":151236,"journal":{"name":"2022 6th International Conference on Green Energy and Applications (ICGEA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126872982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Grey Wolf Optimizer Algorithm for Performance Improvement and Cost Optimization in Microgrids 微电网性能改进和成本优化的灰狼优化算法

2022 6th International Conference on Green Energy and Applications (ICGEA) Pub Date : 2022-03-04 DOI: 10.1109/icgea54406.2022.9791902

Charivil Sojy Rajan, M. Ebenezer

{"title":"Grey Wolf Optimizer Algorithm for Performance Improvement and Cost Optimization in Microgrids","authors":"Charivil Sojy Rajan, M. Ebenezer","doi":"10.1109/icgea54406.2022.9791902","DOIUrl":"https://doi.org/10.1109/icgea54406.2022.9791902","url":null,"abstract":"The traditional grid is undergoing a rapid transition from its conventional unidirectional form to an interactive, smart, bidirectional form. Microgrids are an integral part of smart grids playing a prominent role in supplying power to regions lacking electrical infrastructure. Since there may be diverse Distributed Generation (DG) sources in a microgrid, it is challenging to maintain the bus voltage at the desired value, which may adversely affect the performance of microgrids. This demands the implementation of controllers. The classical PID controller would be an apt choice in such a scenario. To obtain the desired output, it is necessary to perform the tuning of control parameters-proportional, integral and derivative gains, Kp, Ki and Kd, respectively. This paper presents the implementation of Grey Wolf Optimizer (GWO) Algorithm tuned PID Controller to maintain the DC link voltage of a microgrid under study. The latter part of the paper presents a multi-microgrid interconnection scheme. The GWO Algorithm has been implemented for the cost optimization of this multi-microgrid interconnection scheme, consisting of thermal units, solar PV array and wind generation. It has been proved that there is considerable savings in the total cost due to the integration of solar PV array and wind generation. The microgrid modeling and simulations in both cases are performed in the MATLAB/Simulink environment.","PeriodicalId":151236,"journal":{"name":"2022 6th International Conference on Green Energy and Applications (ICGEA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127622164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Investment Planning Model and Economics of Wind-Solar-Storage Hybrid Generation Projects Based on Levelized Cost of Electricity 基于电力成本均等化的风能-太阳能-储能混合发电项目投资规划模型及经济性

2022 6th International Conference on Green Energy and Applications (ICGEA) Pub Date : 2022-03-04 DOI: 10.1109/icgea54406.2022.9791470

Kaiyan Luo, Rui Wang, Qing Liu

引用次数: 2