TOKYO UNIVERSITY OF SCIENCE University Research Administration Center
1-3, Kagurazaka, Shinjuku-ku, Tokyo, 162-8601, Japan E-MAIL: [email protected]
Monitoring and analysis technologies for PV systemsMonitoring and analysis technologies for PV systemsEnergyand
environment
2018.03
Purpose of Research
For great utilization of renewable energy resources, many PV (Photovoltaic) systems, with high reliability and a lifetime of 20 years or more, are expected to be installed. However, daily weather changes can greatly affect their power output, and thus the problem occurs that a PV system may not be noticed. Accordingly, in order to maintain the performance of a PV system for many years, it is essential to monitor the system and analyze the monitoring data. Our group is developing a failure detection system which can monitor and diagnose a wide range of PV systems (from rooftop to mega-solar plants) at low cost and in a simple manner.
To effectively diagnose a PV system, its power output and the energy input (solar irradiance) must be monitored. However, an on-site pyranometer is rarely installed in a typical rooftop PV system. We have developed and are using a Web-based self-diagnosis support system, which diagnose PV systems based on the data from pyranometers installed at nearby weather stations and public buildings. For mega-solar and other large power plants that are often monitored by on-site pyranometry, we are developing a method to detect a small (a few %) power decrease by detailed analysis of data obtained by measuring over periods of 1 min.
Summary of Research
Future Developments
Use satellite data for better solar irradiance estimation. Deploy the self-diagnosis support system throughout Japan.
Associated System:Participated in JST CREST EMS “System Theory for HarmonizedPower System Control Based on Photovoltaic Power Prediction”(April 1, 2015–March 31, 2017) as the chief joint researcher
Yuzuru UEDA (Professor, Department of Electrical Engineering, Faculty of Engineering, Tokyo University of Science)
From web-based self-diagnosis for domestic PV systems to complex analysis of mega-solar plants, the energy conversion of a PV system is analyzed and its health is evaluated using our model. Our model can also predict power output based on weather information with high accuracy.
Make server environment and optimizesystem to enable use of the self-diagnosissupport system by many users. More pyranometer sites required.
Comparison with Conventionalor Competitive Technology
Self-diagnosis support for actual PV systems. Evaluation of health of large PV plants. Pre-construction power generation prediction
and profitability assessment for a new plant.
Expected Applications
Challenges in Implementation
Pyranometer installation and provision of databy power plants. Joint study proposals for server system
installation and web system optimization.
What We Expect from Companies
Advanced analysis system to detect a problem in a PV system based on minimal monitoring data.Points
Module power output (Wh) monitored
System power output (Wh) monitored
Solar irradiation
Measurem
ent error
Difference in ratingsPV conversion efficiency
Sunlightlosses/gains
SystemoutputLosses/gains in light
to electricityconversion
ShadeOptical degradation/dirt
Reflection (incident angle)
Spectral mismatchDegradation/restoration
Non-linearity at low irradiance
Module temp.Array I-V imbalance
DC circuitPCS (inverter)
Maximum output function point mismatch
Measurem
ent error
Analysis error
AC output
• MPPT tracking error I-V curve with steps Fast change System start/low irradiance
• PCS protection function• System voltage• Insufficient PCS capacity