Penerapan Sistem SCADA Dalam Perancangan Model Inferensi Logika Fuzzy Mamdani Pada Pembebanan Trafo Gardu Distribusi

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Rahma Farah Ningrum
Riki Ruli A Siregar
Darma Rusjdi

Abstract

Tujuan penelitian ini membuat prototype sistem SCADA dalam proses sistem kendali dan model logika Fuzzy Mamdani pada pembebanan trafo gardu distribusi berbasis mikrokontroller. Sistem kendali dan pemantauan berbasis Internet of Things (IoT) yang dapat memudahkan. Fungsi utama SCADA yang diterapkan yaitu Penerapan metode logika Fuzzy Mamdani dengan fungsi implikasi menggunakan metode MIN pada Segi Telemetering dengan pengukuran nilai arus dan tegangan, Sedangkan Segi Telekontrolling terdapat pada proses recovery atau menghidupkan dan mematikan pada gardu distribusi saat terjadi gangguan adapun Segi Telesignaling yaitu saat pengiriman sinyal notifikasi untuk mengaktifkan proses recovery gardu saat gangguan. Adapun Akuisisi Data terdapat pada saat penyimpanan data SAIDI SAIFI dan penyimpanan hasil monitoring perangkat. Dari hasil pengujian perangkat keras dan perangkat lunak, terutama dalam pengujian sistem ketika gardu dimatikan proses pemulihan berjalan sesuai dengan skenario awal. Setelah gardu relay dilanjutkan, data disimpan mengikuti waktu mati, seumur hidup, durasi, dan periode data.

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How to Cite
Ningrum, R. F., Siregar, R. R. A., & Rusjdi, D. (2020). Penerapan Sistem SCADA Dalam Perancangan Model Inferensi Logika Fuzzy Mamdani Pada Pembebanan Trafo Gardu Distribusi. PETIR, 13(2), 110–118. https://doi.org/10.33322/petir.v13i2.1001
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References

[1] T. Cruz et al., “A Cybersecurity Detection Framework for Supervisory Control and Data Acquisition Systems,” IEEE Trans. Ind. Informatics, vol. 12, no. 6, pp. 2236–2246, 2016.
[2] A. Ghaleb, S. Zhioua, and A. Almulhem, “SCADA-SST: A SCADA security testbed,” in 2016 World Congress on Industrial Control Systems Security, WCICSS 2016, 2017, pp. 34–39.
[3] P. S. S. Shah, S. Raut, D. Jagadale, A. Khatmode, and H. Patil, “IOT Based Industrial SCADA System,” Int. Res. J. Eng. Technol., vol. 4, no. 4, pp. 2432–2435, 2017.
[4] Y. Chen and W. Pei, “Design and implementation of SCADA system for micro-grid,” Inf. Technol. J., vol. 12, no. 24, pp. 8049–8057, 2013.
[5] B. Atlagic, M. Cokic, and M. Ssagi, “Concept of a SCADA system designed for education and research,” Appl. Microbiol. Biotechnol., vol. 85, no. 1, pp. 2071–2079, 2014.
[6] M. S. Thomas and J. D. McDonald, “SCADA fundamentals,” in Power System SCADA and Smart Grids, 2015, pp. 21–74.
[7] L. A. Maglaras and J. Jiang, “Intrusion detection in SCADA systems using machine learning techniques,” in Proceedings of 2014 Science and Information Conference, SAI 2014, 2014, pp. 626–631.
[8] A. Ujvarosi, “Evolution of SCADA Systems,” Bull. Transilv. Univ. Bra?ov, vol. 9, no. 58, pp. 63--68, 2016.
[9] R. H. McClanahan, “The benefits of networked scada systems utilizing IP-enabled networks,” in Papers - Rural Electric Power Conference, 2002, pp. C5-1.
[10] M. A. A. IAS G.I., LOLEA M.S., “SCENARIOS OF REGIONAL POWER SYSTEM EXPANSION FROM SOUTHERN OF BIHOR COUNTY BASED ON THE EXPLOITATION OF RENEWABLE ENERGY SOURCES,” J. Sustain. ENERGY, vol. 9, no. 2, pp. 93–100, 2018.
[11] I. Allafi and T. Iqbal, “Low-Cost SCADA System Using Arduino and Reliance SCADA for a Stand-Alone Photovoltaic System,” J. Sol. Energy, 2018.
[12] K. S. Budi, S. Muslim, and A. B. Santosa, “Literature Study on the Influence of Arduino Microcontroller Trainer Media on Creative Thinking Level and Student Learning Outcomes in Microcontroller Learning,” in International Symposium on Social Sciences, Education, and Humanities (ISSEH 2018), 2019.
[13] S. S. M. Setiawan Agus, “SIMULASI MIKROKONTROLER PENGUKUR JARAK BERBASIS ARDUINO UNO SEBAGAI MEDIA PEMBELAJARAN MAHASISWA POLITEKNIK HARAPAN BERSAMA,” J. POLEKTRO J. Power Elektron., 2018.
[14] K. E. Holbert, A. Mishra, and L. Mill, “Intrusion detection through SCADA systems using fuzzy logic-based state estimation methods,” Int. J. Crit. Infrastructures, 2007.
[15] Z. Aydogmus, “Implementation of a fuzzy-based level control using SCADA,” Expert Syst. Appl., 2009.
[16] J. H. Horng, “SCADA system of DC motor with implementation of fuzzy logic controller on neural network,” Adv. Eng. Softw., 2002.
[17] P. Pancardo, J. A. Hernández-Nolasco, and F. Acosta-Escalante, “A Fuzzy Logic-Based Personalized Method to Classify Perceived Exertion in Workplaces Using a Wearable Heart Rate Sensor,” Mob. Inf. Syst., vol. 2018, 2018.
[18] L. A. Zadeh, “Outline of a New Approach to the Analysis of Complex Systems and Decision Processes,” IEEE Trans. Syst. Man Cybern., 1973.
[19] H. Medjahed, D. Istrate, J. Boudy, and B. Dorizzi, “Human activities of daily living recognition using fuzzy logic for elderly home monitoring,” in IEEE International Conference on Fuzzy Systems, 2009.
[20] E. Kamel and A. M. Memari, “State-of-the-Art Review of Energy Smart Homes,” J. Archit. Eng., vol. 25, no. 1, p. 03118001, 2019.