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Title:
 
Multiscale Analysis of Silicon-Based Photovoltaic Module Performance in a 19 Years-Old Power Plant
 
Author(s):
 
M. Li, K. Le Dinh, H. Ochiai, I. Kurimoto, A. Fujita, Y. Toda
 
Keywords:
 
Degradation, PV Power Plant, PV Module, IoT, Smart Inspection
 
Topic:
 
Photovoltaic Modules and BoS Components
Subtopic: PV Module Design, Manufacture, Performance and Reliability
Event: 35th European Photovoltaic Solar Energy Conference and Exhibition
Session: 5CV.1.40
 
Pages:
 
1244 - 1246
ISBN: 3-936338-50-7
Paper DOI: 10.4229/35thEUPVSEC20182018-5CV.1.40
 
Price:
 
 
0,00 EUR
 
Document(s): paper
 

Abstract/Summary:


A typical photovoltaic power plant is composed by photovoltaic modules connected both serially and parallelly. This special architecture makes it extremely difficult to inspect performance at module-level. We are developing an intelligent, remote and automatic inspection solution to solve this problem by adopting both Internet of Things technologies and big-data analysis. In this research, we deployed a novel power line communication technology on a vintage power plant about 19 years to collect operating data on module-level. Meanwhile, performance of each module was measured through professional equipment. Through statistical analysis of dynamic operating data of each module and comparison with static performance data, we found that there was a correlation. This result indicates that we may be able to develop a big-data approach to supersede the traditional way of inspecting module performance. In addition, the performance data we obtained from this old power plant showed varying degrees of performance degradation. This difference not only displays the importance of module-level data to power plant performance analysis, but also helps to improve the traditional model of photovoltaic power plant performance prediction under the premise of uniform degradation rate.