I certify that this project report entitled “HIGH-RESOLUTION TEMPORAL SOLAR IRRADIANCE MEASUREMENT” has been prepared by CHEAH KAI YUEN and has met the required standard for submission, partially fulfilling the requirements for the award of Bachelor of Engineering (Honours.) Electrical and Electronics at Tunku Abdul Rahman University. This report is copyrighted by the author under the terms of the Copyright Act 1987, as qualified by the Intellectual Property Policy of Universiti Tunku Abdul Rahman. Due credit will always be given to the use of material contained in or derived from this report.
Lim Boon Han for his invaluable advice, guidance and his enormous patience throughout the development of the research. A high-resolution temporal solar irradiance measurement is needed to study the intermittency of solar power since it has a higher sampling rate. In this paper, a 10 second resolution solar radiation measurement system is built and the collected data is automatically uploaded to the cloud for storage.
Background
The solar radiation value will vary due to the movement of clouds, the quality of air and the presence of tall plants. The brightness index is the ratio of transmitted solar radiation on Earth to extraterrestrial radiation. The areas receiving low solar radiation will have a larger total current harmonic distortion compared to the total voltage harmonic distortion.
In addition, solar irradiance intermittency research is also crucial for predicting the irradiance characteristics of a particular solar power plant. Solar irradiance intermittency is defined as the fluctuation of solar irradiance in a certain area over a certain time span (Vindel and Polo, 2014). The effect of interruption of solar radiation is that it can cause a sudden voltage drop at the output of the PV device.
Importance of the Study
To obtain a complete database, a higher resolution solar radiation measurement system had to be developed. This system should be able to collect a larger amount of solar radiation data within a fixed period, store the collected data in cloud storage, and be convenient for users to access the data. collected even though they are far from the solar site. Throughout this study, more data can be collected as temporal measurement of solar radiation with a higher resolution of 10 seconds is implemented and the data can be stored in the cloud.
Problem Statement
Aim and Objectives
Scope and Limitation of the Study
Introduction
Literature Review
- Solar temporal and spatial characteristics
- Measurement models for predicting the irradiance variability
- Collection of real-time environment data using Raspberry Pi
- High-resolution solar radiation measurement in Singapore
- The differences of high-resolution solar irradiance data collection between ground and satellite-derived
- Generation of Solar Irradiance Data at 10 minutes basis using a new technique
- How solar irradiance intermittency influences the Photovoltaic system
- The effect of compensation of photovoltaic systems with the grid to help to improve the voltage drop problem
A short-term change in solar radiation will affect the efficiency of photovoltaic and concentrating photovoltaic systems. The measurement of solar radiation with high resolution is dominant for studies regarding the effect of PV systems on a grid. The Solar Integration National Database (SIND) method is implemented so that the satellite can collect solar radiation data at a faster rate from 30 minutes to 1 minute.
There will be a slight difference between the solar irradiance measured by ground measurements and the irradiance data obtained from the satellite. This is because the method used to measure solar irradiance variability is different for both satellite and ground-based measurements. Several methods have been proposed for the analysis of solar irradiance data over a shorter time scale.
Some new ideas such as the "smart city" require a higher temporal resolution solar radiation data if they plan to implement photovoltaic technology in the system. Leocadio Hontoria and his team analyzed the solar radiation data from a database in Jaén, Spain. They have the synthetic and actual solar radiation data for January, April and.
The difference between the performance of a battery storage photovoltaic system, which is measured on a minute and hour basis, is studied. In cloudy weather, there will be more fluctuation in the solar radiation data due to the presence of clouds. On December 1, 2012, they simulate on a minute basis the solar radiation and current generated by the PV system.
As can be seen from the graph, the fluctuation of the solar radiation also causes the fluctuation of the photovoltaic current. Based on Figure 12, the fluctuation of solar irradiance and battery current cannot be observed in the hourly data due to the low temporal resolution. Nowadays, more and more methods for measuring solar radiation with high temporal resolution are used around the world.
Overview
Overall circuit construction
First, the 240V AC power supply is used to power the Raspberry Pi 3 B+ and SOZ-03 Silicon solar radiation analog sensor via the 240V AC to 5V DC adapter and 240V AC to 12V DC adapter. Since Raspberry Pi can only receive digital signals and the radiation meter emits analog signals, the signal is converted into digital form via MCP 3002 Analog-to-Digital (ADC) converter. A DS18B20 temperature sensor is used to obtain a more accurate temperature reading and send it to Raspberry Pi.
After collecting the temperature and solar radiation data, a comma-separated value file is created inside Raspberry Pi and it is then sent to cloud storage.
Raspberry Pi 3B+
Setting up Raspberry Pi
VNC (Virtual Network Computing) is a graphical desktop sharing system so that a computer can control another computer over the Internet. SSH (Secure Shell) is enabled to access the remote computer and execute commands. Both VNC and SSH are needed when we need to access the raspberry pi with our own laptop without a monitor, mouse and keyboard.
NES Silicon Solar Radiation Sensor Type SOZ-03
DS18B20 was chosen because it is small, easy to configure and has a more accurate measurement compared to other types of temperature sensors such as DHT 11. Other than that, DS18B20 is also suitable to be implemented in this project because it only outputs digital signals. to the control panel.
MCP3002
Coding
Method of Measurement .1 Method of collecting data
Method of Analysing data
1 minute resolution data is extracted from 10 seconds resolution data by entering the command. The value "6" in the command indicates that the data will be extracted every six rows in 10-second resolution data. To calculate the standard deviation for different temporal resolutions in Microsoft Excel, a command which is "=STDEV.P(IF(data range<>0, data range))" must be entered.
In the command, the range of data means the range of cells for which the standard deviation was to be calculated. Besides that, this command will also ignore all the cells in the range that contain '0' value.
Work plan and Gantt chart
Comparison between Raspberry Pi data and Pyranometer’s data Solar irradiance data were collected at the rooftop of UTAR Sungai Long
Graph Comparison with the pyranometer
The orange lines in the graphs in figures 26, 27 and 28 show the result of the Raspberry Pi and the SOZ-03 solar radiation sensor with a resolution of 10 seconds, while the blue line is the result of the pyranometer with the resolution of 1 minute. The primary y-axis on the left side of the graph represents the solar irradiance range of the pyranometer, while the secondary y-axis on the right side of the graph represents the solar irradiance range of the SOZ-03 and Raspberry Pi. Based on the results obtained in Figure 28, the trend for both temporal resolutions is almost the same.
The difference between the two charts is that the higher resolution chart will have more fluctuation compared to the lower resolution chart. Then, the results obtained from the Raspberry Pi and SOZ-03 irradiance sensor will have a higher solar irradiance reading. This may be due to the different types of measuring cells used to collect solar radiation.
In this project, a monocrystalline measuring cell is used in the solar radiation sensor SOZ-03, which is different from the one used in the pyranometer.
Data logging with the overGrive
Duplicating of three sets of circuits
The reason why this calibration of the three sets is performed one by one is due to the limited space for the setup and lack of extension cord. This percentage difference may be caused by the offset error of the third set of electronic part. So, the calibration of the third has to be adjusted more before it is then placed system to the sites.
Analyzing the collected data from Set 2 comparing to different time resolutions
Thus, a measurement system with a higher time resolution should be applied in the PV industry especially when studying the interruption of solar radiation. Then, the standard deviation of the different time resolution and the maximum difference between the points are calculated and the results are shown in figures 37 and 38. The method of calculating the standard deviation and the maximum differences between the points is presented in sub-chapter 3.9.2.
Based on the graph in Figure 37, it shows that within 15 days, the standard deviation of a higher resolution system is higher. Since a higher resolution measurement system collects more data per day, the data will be more spread out from the average irradiance and thus have a higher standard deviation. Apart from that, in Figure 38, the standard deviation of solar irradiance changes is higher in the lower resolution system.
The frequency of large changes in solar radiation is therefore higher compared to a measurement system with a higher resolution. This proves that the higher resolution measurement system can capture more data with higher accuracy. In addition, according to Figure 39, the maximum difference between points for a higher resolution system is observed to be smaller for most of the day.
The graph in the figure excludes the analysis for 30-minute data because the 30-minute resolution is too low compared to the others. Finally, Figure 40 shows that the solar irradiation frequency changes in excess of 100 W/m2 based on the different time resolution measurement system. According to the line graph, the higher the resolution of the solar irradiance measurement, the higher the frequency of changes in solar irradiance, which exceeds 100 W/m2.
Conclusion
Skills to build a simple yet reliable high temporal resolution solar radiation measurement system are learned.
Future improvement
Spatial and temporal variability in the solar energy resource: Assessing the value of short-term measurements at potential solar installation sites. Comparative study for time-specific Ross coefficient and overall Ross coefficient for estimation of photovoltaic module temperature. The effect of irradiance and temperature on the performance of monocrystalline silicon solar module in Kakamega.
