URN |
etd-0603118-141159 |
Author |
Wei-Hao Huang |
Author's Email Address |
No Public. |
Statistics |
This thesis had been viewed 5571 times. Download 0 times. |
Department |
Electrical Engineering |
Year |
2017 |
Semester |
2 |
Degree |
Ph.D. |
Type of Document |
|
Language |
zh-TW.Big5 Chinese |
Title |
Global Maximum Power Point Tracking for Photovoltaic Generation Systems Using Shading Detection and State Estimation |
Date of Defense |
2018-06-25 |
Page Count |
127 |
Keyword |
Photovoltaic Generation System
Partial Shading
Global Maximum Power Point Tracking
State Estimation
Section Prediction Metho
|
Abstract |
Photovoltaic modules need to have the permanent ability to resist environmental alteration and supply stable power. Output power improvement of Photovoltaic Generation Systems (PVGSs) can not only raise the practicality of PVGSs but also increase the industry competitiveness. To increase the output power of PVGSs, the effect of environmental factors especially the Partially Shaded Conditions (PSC) should be further investigated. This dissertation proposes a Global Maximum Power Point (GMPP) tracking algorithm for PVGSs using shading detection and state estimation. Using the captured voltages and currents from a PVGS, the proposed state estimation can be used to calculate the approximate solar irradiance, ambient temperature and other PVGS’s parameters. In this way, the maximum power point can be calculated and tracked efficiently. The proposed tracking algorithm consists of three stages. Stage I is the parameter correction of PVGS. The purpose is to correct the PVGS’s parameters to meet the characteristic curve of PVGSs manufactured by different vendors. Stage II is shading detection used to diagnose whether a PVGS is under PSC. Stage III is GMPP tracking that utilizes the capatured voltages and currents and state estimation to find out the GMPP. A Segment Prediction Method (SPM) is proposed to predict the GMPP segment from Current-Voltage (I-V) characteristic curve and to enhance the tracking performance. Using shading detection as proposed in Stage II, if the PVGS is not under PSC, two captured voltages and currents are enough to calculate the GMPP without executing SPM. The transient tracking time can be effective shortened. When the PVGS is under PSC, the global maximum power point tracking as proposed in Statge III can use SPM to quickly predict the GMPP segment. The tracking time can also be effectively reduced since the proposed SPM does not need to scan all segments for GMPP tracking. Simulation and experimental results show that PSC can be effectively detected and more than 99% tracking accuracy and lower tracking losses are achieved by the proposed tracking algorithm regardless of PSC or not. |
Advisory Committee |
Chih-Chiang Hua - chair
Yi-Hua Liu - co-chair
Rong-Ceng Leou - co-chair
Tzung-Lin Lee - co-chair
Shun-Chung Wang - co-chair
Yao-Ching Hsieh - co-chair
Jen-Hao Teng - advisor
|
Files |
Indicate in-campus at 5 year and off-campus access at 5 year. |
Date of Submission |
2018-07-03 |