Implementasi Novel Bat Algorithm Untuk Penjadwalan Ekonomis Pembangkit Listrik Termal Dengan Integrasi PLTB
Abstract
Economic dispatch aims to control the variables of the power system so that the power plants can generate maximally based on load demand according to the characteristics of each plant and with cheaper production costs. In this study, economic dispatch is applied to thermal power plants with the integration of Wind Power Plants (PLTB) in Sulselrabar 150kV power system using the Novel Bat Algorithm (NBA) optimization method, considering voltage stability. The generation cost that can be reduced using the NBA method is IDR 12,583,781 per hour compared to the results of the existing system. With the integration of 100% of the PLTB capacity, the NBA method still provides cheaper economic dispatch results. Using the NBA method, the generation cost can be reduced by IDR 29,854,367 compared to the results of the existing system. After the integration of 100% of the PLTB capacity, the power losses obtained are smaller than before the integration of the PLTB. The system bus voltage conditions before and after the integration of the PLTB are also in good condition as they are within the voltage regulation limits set by PLN, which are +5% and -10%
References
Dwi Putra, M. S., & Abadi, S. (2023). Penjadwalan Ekonomis Pada Pembangkit Termal Dengan Menggunakan Particle Swarm Optimization. Jurnal Teknik Mesin Sinergi, 21(1), 156. https://doi.org/10.31963/sinergi.v21i1.4239
Chen, H., Zhang, R., Li, G., Bai, L., & Li, F. (2016). Economic dispatch of wind integrated power systems with energy storage considering composite operating costs. IET Generation, Transmission and Distribution, 10(5), 1294–1303. https://doi.org/10.1049/iet-gtd.2015.0410
Dey*, S. K., Dash, D. P., & Basu, M. (2020). Economic Environmental Dispatch of Wind Integrated Thermal Power System. International Journal of Recent Technology and Engineering (IJRTE), 8(6), 5186–5192. https://doi.org/10.35940/ijrte.f9528.038620
Fitri, S. N., Akil, Y. S., & Gunadin, I. C. (2018). Economic Dispatch using Novel Bat Algorithm Constrained by Voltage Stability. Proceedings - 2nd East Indonesia Conference on Computer and Information Technology: Internet of Things for Industry, EIConCIT 2018, 163–167. https://doi.org/10.1109/EIConCIT.2018.8878604
Haripuddin, H., Riska, M., & Muchtar, A. (2021). Implementasi Metode Lalat Buah dalam Penjadwalan Ekonomis Pembangkit pada Sistem Tenaga Listrik. Seminar Nasional LP2M UNM. https://ojs.unm.ac.id/semnaslemlit/article/download/25253/12633
Ibrahim, R. S., Wibowo, R. S., & Musthofa, A. (2017). Economic Load Dispatch Unit Pembangkit Termal Mempertimbangkan Penambahan Pembangkit Tenaga Angin Dengan Menggunakan Firefly Algorithm. Jurnal Teknik ITS, 6(1). https://doi.org/10.12962/j23373539.v6i1.21189
Jayabarathi, T., Raghunathan, T., Adarsh, B. R., & Suganthan, P. N. (2016). Economic dispatch using hybrid grey wolf optimizer. Energy, 111, 630–641. https://doi.org/10.1016/j.energy.2016.05.105
Meng, X. B., Gao, X. Z., Liu, Y., & Zhang, H. (2015). A novel bat algorithm with habitat selection and Doppler effect in echoes for optimization. Expert Systems with Applications, 42(17–18), 6350–6364. https://doi.org/10.1016/j.eswa.2015.04.026
Nazari-Heris, M., Mehdinejad, M., Mohammadi-Ivatloo, B., & Babamalek-Gharehpetian, G. (2019). Combined heat and power economic dispatch problem solution by implementation of whale optimization method. Neural Computing and Applications, 31(2), 421–436. https://doi.org/10.1007/s00521-017-3074-9
Nguyen, T. T., Nguyen, T. T., & Vo, D. N. (2018). An effective cuckoo search algorithm for large-scale combined heat and power economic dispatch problem. Neural Computing and Applications, 30(11), 3545–3564. https://doi.org/10.1007/s00521-017-2941-8
Riswandi, S., Lubis, R. S., & Syukri, M. (2021). Operasi Ekonomis Pada Sistem Pembangkit Thermal Sumatera Barat Dengan Menggunakan Metode Iterasi Lambda. Jurnal Komputer, Informasi Teknologi, Dan Elektro, 6(1), 19–25. https://doi.org/10.24815/kitektro.v6i1.20719
Sharifi, S., Sedaghat, M., Farhadi, P., Ghadimi, N., & Taheri, B. (2017). Environmental economic dispatch using improved artificial bee colony algorithm. Evolving Systems, 8(3), 233–242. https://doi.org/10.1007/s12530-017-9189-5
Sonmez, Y., Kahraman, H. T., Dosoglu, M. K., Guvenc, U., & Duman, S. (2017). Symbiotic organisms search algorithm for dynamic economic dispatch with valve-point effects. Journal of Experimental and Theoretical Artificial Intelligence, 29(3), 495–515. https://doi.org/10.1080/0952813X.2016.1198935
Arief, A., Nappu, M. B., Mustafa, S., Erwin, & Thaha, S. (2022). Optimal capacitor placement in a dominant induction motor loads power system. Energy Reports, 8, 592–597. https://doi.org/10.1016/j.egyr.2022.10.254
Vijayaraj, S., & Santhi, R. K. (2016). Multi-area economic dispatch using flower pollination algorithm. International Conference on Electrical, Electronics, and Optimization Techniques, ICEEOT 2016, 4355–4360. https://doi.org/10.1109/ICEEOT.2016.7755541
Xiong, G., & Shi, D. (2018). Orthogonal learning competitive swarm optimizer for economic dispatch problems. Applied Soft Computing Journal, 66, 134–148. https://doi.org/10.1016/j.asoc.2018.02.019
