DEVELOPMENT OF SOLAR POWER SYSTEMS CONDITION MONITORING BASED ON THE INTERNET OF THINGS AND THE BIG DATA PLATFORM
The National Energy General Plan (RUEN) in 2017 targets the use of more than 66% renewable energy by 2050. As a tropical country, Indonesia has a solar energy potential of more than 400 GW. Solar energy is intermittent so its development will continue to be carried out by increasing the efficiency o...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/83691 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The National Energy General Plan (RUEN) in 2017 targets the use of more than 66% renewable energy by 2050. As a tropical country, Indonesia has a solar energy potential of more than 400 GW. Solar energy is intermittent so its development will continue to be carried out by increasing the efficiency of solar panel production. The greater the development of PLTS, further technology will be needed to monitor the performance of the PLTS system so that it will make it easier to detect failures and observe system performance in real time and online.
This research aims to develop and analyze the performance of an Internet of Things (IoT) based Solar Power Plant (SPP) condition monitoring system at the Villa Merah Building, ITB. The research methodology includes data collection from an inverter, data processing using the Python programming language, data storage in MySQL, and data visualization using the grafana platform. System testing is carried out to measure data accuracy, data volume, delay time and data speed.
The test results show that the developed system is capable of acquiring and monitoring data accurately with an average data volume of 0.07 KB, a delay time of 1.06 seconds, and a data speed of 0.06 KB/second. Data accuracy analysis shows the MAE is 2.29 Volts for both strings, which shows that the system is able to monitor the condition of the PLTS well. The conclusion of this research is that the IoT-based PLTS condition monitoring system developed is capable of acquiring data using the Modbus TCP protocol, processing the data using Python, storing it in MySQL, and visualizing it in real-time using Grafana. Then performance analysis shows that the average data volume produced is 0.07 KB, the delay time is 1.06 seconds, and the data speed is 0.06 KB/second. Suggestions for further research are integration with energy management systems in buildings and development of notification features for certain conditions in PLTS systems.
Keywords: Solar Power Plant, internet of Things (IOT), performance monitoring, data acquisition, and data visualization
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