Study of joint temporal-spatial distribution of array output for large-scale photovoltaic plant and its fault diagnosis application
Authors:
- Honglu ZhuHZHonglu Zhu
- Haizheng WangHWHaizheng Wang
- Dahai KangDKDahai Kang
- Lizhong ZhangLZLizhong Zhang
- Lingxing LuLLLingxing Lu
- Jianxi YaoJianxi Yao
- Yang HuYHYang Hu
- 1 March 2019
- journal article
- research article
- Published by Elsevier in Solar Energy
- Vol. 181, 137-147
Abstract
No abstract availableKeywords
Funding Information
- State Grid Corporation of China (SGHADK00PJJS1800072)
This publication has 20 references indexed in Scilit:
- Photovoltaic fault detection algorithm based on theoretical curves modelling and fuzzy classification systemEnergy, 2017
- An enhanced machine learning based approach for failures detection and diagnosis of PV systemsEnergy Conversion and Management, 2017
- Online modular level fault detection algorithm for grid-tied and off-grid PV systemsSolar Energy, 2017
- Intelligent fault diagnosis of photovoltaic arrays based on optimized kernel extreme learning machine and I-V characteristicsApplied Energy, 2017
- Statistical fault detection in photovoltaic systemsSolar Energy, 2017
- Photovoltaic Array Fault Detection by Automatic ReconfigurationEnergies, 2017
- Real Time Fault Detection in Photovoltaic SystemsEnergy Procedia, 2017
- A Heuristic Diagnostic Method for a PV System: Triple-Layered Particle Swarm Optimization–Back-Propagation Neural NetworkEnergies, 2017
- A novel fault diagnosis technique for photovoltaic systems based on artificial neural networksRenewable Energy, 2016
- Applications of fuzzy logic in renewable energy systems – A reviewRenewable and Sustainable Energy Reviews, 2015