Lux and current analysis on lab-scale smart grid system using Mamdani fuzzy logic controller

• Published in: Journal of Mechatronics, Electrical Power, and Vehicular Technology
• Main Author: Prasetyo B.; Aziz F.S.; Handayani A.N.; Priharta A.; Che Ani A.I.B.
• Format: Article
• Language: English
• Published: National Research and Innovation Agency (BRIN) 2020
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150916892&doi=10.14203%2fj.mev.2020.v11.11-21&partnerID=40&md5=cecb90c8529eaacfddd754b741c6eea6

The increasing need for electrical energy requires suppliers to innovate in developing electric distribution systems that are better in terms of quality and affordability. In its development, it is necessary to have a control that can combine the electricity network from renewable energy and the main network through voltage back-up or synchronization automatically. The purpose of this research is to create an innovative lux and current analysis on a lab-scale smart grid system using a fuzzy logic controller to control the main network, solar panel network and generator network to supply each other with lab-scale electrical energy. In the control, Mamdani fuzzy logic controller method is used as the basis for determining the smart grid system control problem solving by adjusting the current conditions on the main network and the light intensity conditions on the LDR sensor. Current conditions are classified in three conditions namely safe, warning, and trip. Meanwhile, the light intensity conditions are classified into three conditions namely dark, cloudy and bright. From the test results, the utility grid (PLN) is at active conditions when the load current is 0.4 A (safe) and light intensity is 1,167 Lux (dark). Then the PLN + PV condition is active when the load current is 1.37 (warning) and the light intensity is 8,680 lux (bright). Finally, the generator condition is active when the load current is 1.6 (trip) and the light intensity is 8,680 (bright). Based on the test results, it is known that the system can work to determine which source is more efficient based on the parameters obtained. © 2020 Research Center for Electrical Power and Mechatronics-Indonesian Institute of Sciences.