Modeling an Intelligent Solar Power Plant Control System Using Colored Petri Nets

Author(s):  
Aleksandr Gozhyj ◽  
Irina Kalinina ◽  
Vladyslav Nechakhin ◽  
Victor Gozhyj ◽  
Victoria Vysotska
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.


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