Main Article Content


Prediction of electrical load on 150 kV Sulselrabar electrical system, analyzed using approach at night peak load using Fuzzy Logic based intelligent method. The peak load characteristics are certainly different from the load in normal time, therefore a special approach is needed to predict the peak night load. As input data will be used data of night peak load in 2010 until 2015, on the same day and date, each 4 days before day-H or day date which will be predicted load. For the data processing stage is divided into several stages, namely pre-processing, processing, and post-processing. The load data processing follows several procedures, ie computing WDmax, LDmax, TLDmax and VLDmax each year. Data processing is processed using excel software and then using Matlab software to run Fuzzy Logic. From the analysis results obtained, Error Prediction The peak evening load is very small that is equal to -0.070033687%. As comparison data used actual day-H data is April 2016. The graph of analysis result also shown in this paper.

Keywords– Fuzzy Logic Control, Load Forecasting, Error, VLDmax

Article Details

Author Biographies

Muhammad Ruswandi Djalal, State Polytechnic of Ujung Pandang

Department of Energy Engineering

Andareas Pangkung, State Polytechnic of Ujung Pandang

Department of Energy Engineering

Sonong Sonong, State Polytechnic of Ujung Pandang

Department of Energy Engineering

Apollo Apollo, State Polytechnic of Ujung Pandang

Department of Energy Engineering
How to Cite
Djalal, M. R., Pangkung, A., Sonong, S., & Apollo, A. (2018). Peak Load Prediction Using Fuzzy Logic For The 150 kV Sulselrabar System. Journal of Information Technology and Computer Science, 3(1), 49–59.


  1. 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.
  2. 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 Electronic Engineering-UMSIDA, vol. 1, pp. 1-7, 2017.
  3. M. R. Djalal, M. A. Haikal, T. M. P. N. U. Pandang, and T. E. I. P. Aceh, "Penyelesaian Aliran Daya 37 Bus Dengan Metode Newton Raphson (Studi Kasus Sistem Interkoneksi 150 kV Sulawesi Selatan)," Jurnal Teknik Mesin SINERGI, vol. 12, pp. 35-49, 2014.
  4. C. P. Putra, M. Tuegeh, H. Tumaliang, and L. S. Patras, "Analisa Pertumbuhan Beban Terhadap Ketersediaan Energi Listrik di Sistem Kelistrikan Sulawesi Selatan," E-JOURNAL TEKNIK ELEKTRO DAN KOMPUTER, vol. 3, pp. 19-30, 2014.
  5. a. admsin, "Penentuan Breaking Capacity Circuit Breaker pada Bus Sistem Sulselrabar," Jurnal Teknik Mesin SINERGI, 2012.
  6. D. WICAKSONO, "Perencanaan pemeliharaan unit pembangkit dengan menggunakan metode Levelized Risk:: Studi kasus di PT PLN (Persero) wilayah Sulselrabar," Universitas Gadjah Mada, 2007.
  7. M. R. Djalal, M. Y. Yunus, H. Nawir, and A. Imran, "Application of Smart Bats Algorithm for Optimal Design of Power Stabilizer System at Sengkang Power Plant," International Journal of Artificial Intelligence Research, vol. 1, 2017.
  8. 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.
  9. 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.
  10. M. Hidayat, Y. S. Akil, I. Gunadin, and M. R. Djalal, "Short-Term Electricity Demand Forecasting using Fuzzy Logic-Flower Pollination Algorithm (FL-FPA)," presented at the The 2nd International Conference on Education, Science, and Technology (ICEST) 2017, Four Points by Sheraton, 2017.
  11. I. Gunadin, Y. S. Akil, Sirajuddin, and M. R. Djalal, "Application Fuzzy Logic-Cuckoo Search Algorithm for Load Forecasting in 150 kV Sulselrabar Electric Power System," presented at the The 2nd International Conference on Education, Science, and Technology (ICEST) 2017, Four Points by Sheraton, 2017.
  12. M. R. Djalal and F. 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, pp. 154-165%@ 2541-5832, 2017-12-05 2017.
  13. Y. Hida, R. Yokoyama, K. Iba, K. Tanaka, and K. Yabe, "Load forecasting on demand side by multi-regression model for operation of battery energy storage system," in Universities Power Engineering Conference (UPEC), 2009 Proceedings of the 44th International, 2009, pp. 1-5.
  14. B.-J. Chen and M.-W. Chang, "Load forecasting using support vector machines: A study on EUNITE competition 2001," IEEE transactions on power systems, vol. 19, pp. 1821-1830, 2004.
  15. T. Nguyen and Y. Liao, "Short-Term Load Forecasting Based on Adaptive Neuro-Fuzzy Inference System," JCP, vol. 6, pp. 2267-2271, 2011.
  16. A. Tehlan and V. Kumar, "Fuzzy logic based Load Forecasting," International Journal of Applied Engineering Research, vol. 11, pp. 6625-6626, 2016.
  17. C. S. Carlson, "Fuzzy logic load forecasting with genetic algorithm parameter adjustment," 2012.
  18. A. K. Gangwar and F. Chishti, "Electric Load Forecasting Using Genetic Algorithm–A Review," International Journal of Modern Engineering Research (IJMER), vol. 1, pp. 15-20.
  19. A. Singh and V. K. Tripathi, "Load Forecasting Using Multi-Layer Perceptron Neural Network," International Journal of Engineering Science, vol. 5463, 2016.
  20. W. Charytoniuk and M.-S. Chen, "Very short-term load forecasting using artificial neural networks," IEEE transactions on Power Systems, vol. 15, pp. 263-268, 2000.
  21. A. Kavousi-Fard, H. Samet, and F. Marzbani, "A new hybrid modified firefly algorithm and support vector regression model for accurate short term load forecasting," Expert systems with applications, vol. 41, pp. 6047-6056, 2014.