GRID TIE Solar Power Plant Data Acquisition System using Internet of Things

Author(s):  
Anupama Patil ◽  
Sanjay A. Deokar ◽  
Abuzer Banderkar
2019 ◽  
Vol 8 (2) ◽  
pp. 177-186 ◽  
Author(s):  
Wenhao Li ◽  
Qisheng Zhang ◽  
Qimao Zhang ◽  
Feng Guo ◽  
Shuaiqing Qiao ◽  
...  

Abstract. The ambiguity of geophysical inversions, which is based on a single geophysical method, is a long-standing problem in geophysical exploration. Therefore, multi-method geophysical prospecting has become a popular topic. In multi-method geophysical prospecting, the joint inversion of seismic and electric data has been extensively researched for decades. However, the methods used for hybrid seismic–electric data acquisition that form the base for multi-method geophysical prospecting techniques have not yet been explored in detail. In this work, we developed a distributed, high-precision, hybrid seismic–electrical data acquisition system using advanced Narrowband Internet of Things (NB-IoT) technology. The system was equipped with a hybrid data acquisition board, a high-performance embedded motherboard based on field-programmable gate array, an advanced RISC machine, and host software. The data acquisition board used an ADS1278 24 bit analog-to-digital converter and FPGA-based digital filtering techniques to perform high-precision data acquisition. The equivalent input noise of the data acquisition board was only 0.5 µV with a sampling rate of 1000 samples per second and front-end gain of 40 dB. The multiple data acquisition stations of our system were synchronized using oven-controlled crystal oscillators and global positioning system technologies. Consequently, the clock frequency error of the system was less than 10−9 Hz at 1 Hz after calibration, and the synchronization accuracy of the data acquisition stations was ±200 ns. The use of sophisticated NB-IoT technologies allowed the long-distance wireless communication between the control center and the data acquisition stations. In validation experiments, it was found that our system was operationally stable and reliable, produced highly accurate data, and it was functionally flexible and convenient. Furthermore, using this system, it is also possible to monitor the real-time quality of data acquisition processes. We believe that the results obtained in this study will drive the advancement of prospective integrated seismic–electrical technologies and promote the use of IoT technologies in geophysical instrumentation.


Teknik ◽  
2021 ◽  
Vol 42 (1) ◽  
pp. 35-44
Author(s):  
Riza Alfita ◽  
Koko Joni ◽  
Fajar Dwika Darmawan

Internet of Things technology in this research is utilized on solar power plant (Case Study: Electrical Engineering Department of Trunojoyo Madura University) as a battery power monitoring and load control system. All of these systems were built to make it easier for users to manage the power consumption while preventing battery damage so that lifetime can last longer and the use of PLTS than more optimal. All of these systems are designed to use several integrated components with their respective functions, including Raspberry as a data processing, smartphone as an interface, and sensors actuator as input-output. From the results of the monitoring accuracy test, the average error value is 1.56%. After ensuring the system has a high level of accuracy, The charge-discharge test is conducted in real-time for 7 days, which shows that the system works according to the research objectives as evidenced by the nothingness of power consumption exceeding the SOC standard limit battery used by 30%. Meanwhile, for the control system test, the wifi connection has the fastest average delay for 10,30 s, provider A 11,17 s, and provider B 12,60 s.


Sign in / Sign up

Export Citation Format

Share Document