Cited by Shading type and severity diagnosis in photovoltaic systems via I-V curve imaging and two-stream deep neural network

A Hybrid Spatiotemporal Distribution Forecast Methodology for Ies Vulnerabilities Under Uncertain and Imprecise Space-Air-Ground Monitoring Data Scenarios DOI

Chenhao Sun,

Wang Yaoding,

Xiangjun Zeng

и другие.

Опубликована: Янв. 1, 2024

The weak spots in an integrated energy system (IES) that may jeopardize the overall reliability call for timely and ecient Inspection Maintenance (I&M). One core step here is reasonable allocation deployment of limited I&M personnel or apparatus to regions periods with higher event risks, which requires a pinpoint spatiotemporal distribution forecast future vulnerabilities. For this purpose, paper presents hybrid methodology, Saliency-Rough Fuzzy Utility Pattern recognition (SRFUPr) ensemble, light space-air-ground multi-source-heterogeneous input data. To enhance its eciency productivity, parallel learning architecture identi es critical components yields instead frequencies, established. In case, more quantitative qualitative evaluations can be carried out concurrently. cope potential imprecise uncertain data scenes: assessments, both failure hazard path sets survival function likelihood boxes are incorporated designed relative path-Fussell Vesely Saliency (rp-FVS) model, consider direct impact component itself on reliability, as well indirect impacts from imprecision; analyses, underlying perilous distinguished via combination variable precision-rough model where fuzzy weights worked appropriately line their productiveness level rather than merely manual assumptions, rp-FVS-based inference logic all membership functions con gured identically according components' uncertainty. These two parts will then into rough-fuzzy Measure (RFUM) discover concealed component-vulnerability interconnection patterns. Finally, empirical case study conducted validate comprehensiveness feasibility methodology during real scenes.

Язык: Английский

Процитировано

An Enhanced Buck-Boost Converter for Photovoltaic Diagnosis Application: Accurate MPP Tracker and I-V Tracer DOI

Yassine Chouay, Mohammed Ouassaid

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

A multi-objective pelican optimization algorithm for dynamic reconfiguration of multi-type rural rooftop PV array DOI

Lingzhi Yi,

Siyue Cheng,

Yahui Wang

и другие.

Journal of Intelligent & Fuzzy Systems, Год журнала: 2024, Номер 47(5-6), С. 393 - 409

Опубликована: Дек. 27, 2024

Язык: Английский

Процитировано

Shading type and severity diagnosis in photovoltaic systems via I-V curve imaging and two-stream deep neural network DOI

Zengxiang He, Hongcai Chen, Shuo Shan

и другие.

Energy Conversion and Management, Год журнала: 2024, Номер 324, С. 119311 - 119311

Опубликована: Ноя. 29, 2024

Язык: Английский

Процитировано