Electrical Daily Load Forecasting In Ramadhan Using Type-2 Fuzzy Logic In Sulselrabar System

  • Marhatang Marhatang
  • Muhammad Ruswandi Djalal Politeknik Negeri Ujung Pandang
  • Herman Nawir
  • Sonong Sonong

Abstract

 This study discusses the daily electricity load forecasting 24 hours on 150 kV electric power systems sulselrabar. Forecasting electrical load requires the accuracy of the results with a small error. Peak load forecasting methods used to use smart methods Interval Type-1 Fuzzy Logic (IT1FL) and Interval Type-2 Fuzzy Logic (IT2FL) to predict the needs of the electrical load 1 Ramadan 2016. As input data, it was used load data from 2012 through 2016 for the same day each 1st of Ramadan each year, and as comparative data, it was used actual load data 1, 2016. For the Ramadan input variable, it was used two of the data Variation Load Difference (VLD Max) 2015 as an input variable X, VLD Max 2016 as an input variable Y. From the simulation results obtained highly accurate results where each method produces a very small error, where for methods of using IT1FL of 1.607778264% while using IT2FL by, 1.344510913%.

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References

[1] A. Srivastava, A. S. Pandey, and D. Singh, "Short-term load forecasting methods: A review," in Emerging Trends in Electrical Electronics & Sustainable Energy Systems (ICETEESES), International Conference on, 2016, pp. 130-138.
[2] A. Jain, E. Srinivas, and S. kumar Kukkadapu, "Fuzzy based day ahead prediction of electric load using mahalanobis distance," in Power System Technology (POWERCON), 2010 International Conference on, 2010, pp. 1-6.
[3] S. K. Panda, S. N. Mohanty, and A. K. Jagadev, "Long Term Electrical Load Forecasting: An Empirical Study across Techniques and Domains," Indian Journal of Science and Technology, vol. 10, 2017.
[4] A. Ramadhani, Agus Dharma, & Imam Robandi, "Optimization FOU of Interval Type-2 Fuzzy Inference System Using Big Bang – Big Crunch Algorithm for Short Term Load Forecasting on National Holiday Case Study: South and Central Kalimantan-Indonesia," International Review of Electrical Engineering (IREE), vol. 10, pp. 123-130, 2015.
[5] A. Khosravi and S. Nahavandi, "Load forecasting using interval type-2 fuzzy logic systems: Optimal type reduction," IEEE Transactions on Industrial Informatics, vol. 10, pp. 1055-1063, 2014.
[6] J. Zhao and L. Jiang, "Forecasting Of Type-2 Fuzzy Electric Power System Based On Phase Space Reconstruction Model," network security, vol. 8, 2015.
[7] S. Hassan, A. Khosravi, J. Jaafar, and M. A. Khanesar, "Hybrid model for the training of interval type-2 fuzzy logic system," in International Conference on Neural Information Processing, 2015, pp. 644-653.
[8] E. Kayacan, S. Coupland, R. John, and M. A. Khanesar, "Elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction," in Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on, 2017, pp. 1-7.
[9] S. Hassan, A. Khosravi, and J. Jaafar, "Training of interval type-2 fuzzy logic system using extreme learning machine for load forecasting," in Proceedings of the 9th International Conference on Ubiquitous Information Management and Communication, 2015, p. 87.
[10] M. Y. Yunus, M. R. Djalal, and Marhatang, "Optimal Design Power System Stabilizer Using Firefly Algorithm in Interconnected 150 kV Sulselrabar System, Indonesia," International Review of Electrical Engineering (IREE), vol. 12, pp. 250-259, 2017.
[11] M. R. Djalal, D. Ajiatmo, A. Imran, and I. Robandi, "Desain Optimal Kontroler PID Motor DC Menggunakan Cuckoo Search Algorithm," SENTIA 2015, vol. 7, 2015.
[12] M. R. Djalal, A. Imran, and I. Robandi, "Optimal placement and tuning power system stabilizer using Participation Factor and Imperialist Competitive Algorithm in 150 kV South of Sulawesi system," in Intelligent Technology and Its Applications (ISITIA), 2015 International Seminar on, 2015, pp. 147-152.
[13] M. R. Djalal, H. Nawir, H. Setiadi, and A. Imran, "An Approach Transient Stability Analysis Using Equivalent Impedance Modified in 150 kV South of Sulawesi System," Journal of Electrical and Electronics Engineering UMSIDA, vol. 1, pp. 1-7, 2016.
[14] M. R. Djalal, H. Setiadi, D. Lastomo, and M. Y. Yunus, "Modal Analysis and Stability Enhancement of 150 kV Sulselrabar Electrical System using PSS and RFB based on Cuckoo Search Algorithm," International Journal on Electrical Engineering and Informatics, vol. 9, pp. 800-812, 2017.
[15] M. R. Djalal, M. Y. Yunus, H. Setiadi, and A. U. Krismanto, "Small-Signal-Stability Enhancement using a Power-System Stabilizer based on the Cuckoo-Search Algorithm against Contingency N-1 in the Sulselrabar 150-kV System," Makara Journal of Technology, vol. 22, pp. 1-8, 2018.
[16] M. R. Djalal, M. Y. Yunus, H. Nawir, and A. Imran, "Optimal Design of Power System Stabilizer In Bakaru Power Plant Using Bat Algorithm," 2017, vol. 1, p. 6, 2017-11-10 2017.
[17] U. Umoh, I. Umoeka, M. Ntekop, and E. Babalola, "INTERVAL TYPE-2 FUZZY NEURAL NETWORKS FOR SHORT-TERM ELECTRIC LOAD FORECASTING: A COMPARATIVE STUDY."
[18] N. Ammar, M. Sulaiman, and A. F. M. Nor, "Analysis Load Forecasting of Power System Using of Fuzzy Logic and Artificial Neural Network," Journal of Telecommunication, Electronic and Computer Engineering (JTEC), vol. 9, pp. 181-192, 2017.
[19] D. Ali, M. Yohanna, P. M. Ijasini, and M. B. Garkida, "Application of fuzzy–Neuro to model weather parameter variability impacts on electrical load based on long-term forecasting," Alexandria Engineering Journal, 2017.
[20] D. Ali, M. Yohanna, P. M. Ijasini, and M. B. Garkida, "Application of fuzzy–Neuro to model weather parameter variability impacts on electrical load based on long-term forecasting," Alexandria engineering journal, vol. 57, pp. 223-233, 2018.
[21] A. T. Ali, E. B. Tayeb, and Z. M. Shamseldin, "Short term Electrical Load Forecasting Using Fuzzy Logic," International Journal Of Advancement In Engineering Technology, Management and Applied Science (IJAETMAS), vol. 3, 2016.
[22] F. Tuaimah, "Iraqi Short Term Electrical Load Forecasting Based On Interval Type-2 Fuzzy Logic," World Academy of Science, Engineering and Technology, International Science Index 92, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol. 8, pp. 1255 - 1261, 2014.
[23] M. R. Djalal and Faisal, "Intelligent Fuzzy Logic-Cuckoo Search Algorithm Method for Short-Term Electric Load Forecasting in 150 kV Sulselrabar System," Lontar Komputer: Jurnal Ilmiah Teknologi Informasi, vol. 8, pp. 154-165, 2017.
Published
2018-12-21
How to Cite
MARHATANG, Marhatang et al. Electrical Daily Load Forecasting In Ramadhan Using Type-2 Fuzzy Logic In Sulselrabar System. Lontar Komputer : Jurnal Ilmiah Teknologi Informasi, [S.l.], p. 146-157, dec. 2018. ISSN 2541-5832. Available at: <https://ojs.unud.ac.id/index.php/lontar/article/view/40042>. Date accessed: 21 nov. 2024. doi: https://doi.org/10.24843/LKJITI.2018.v09.i03.p04.
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Articles