Optimization Economic and Emissions of Hydro and Thermal Power Plants in 150 kV Systems Using the Dragonfly Algorithm

Bayu Setyo Wibowo, Susatyo Handoko, Hermawan Hermawan

Abstract


Electricity is one of the energies required by daily living since the greater demand for electricity increases greenhouse emissions that create emission gases resulting in global climate change. The main portion of the output cost is fuel's cost to manufacture electrical energy in thermal turbines. The use of electrical energy is currently rising increasingly following the increasing population. The research aims to optimize hydro generation to minimize thermal generation expense and address economic problems and pollution from shipping. With 2016b using Matlab applications and the lambda iteration process, the analysis method uses the Dragonfly Algorithm method. The analysis found that the average cost of fuel consumption provided by the Dragonfly Algorithm method was IDR 151,164,418 per day with an emission of 917.40 tons per day, based on the simulation results the Dragonfly Algorithm in testing by considering the emission of 5 practical steps. Meanwhile, with the emission of 918,044 tonnes per day, the average cost of fuel consumption produced by the Lambda Iteration method is IDR 151,202,209 per day. Test results can enhance the fuel consumption cost of IDR 37,791 and emissions of 0.641 tons with the Dragonfly Algorithm process.


Keywords


Electricity, Economic and Emissions dispatch, Dragonfly Algorithm

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References


H. Sutanto, T. Haryono, and A. A. Setiawan, “OPTIMASI PENJADWALAN PADA PEMBANGKIT DI JARINGAN 500 kV JAWA-BALI UNTUK MENGURANGI EMISI CO2 MENGGUNAKAN MATPOWER 5.0,” vol. 17, no. 4, pp. 199–205, 2015, doi: 10.12777/transmisi.17.4.199-205.

PLN, “Perspektif Pengembangan Sistem Ketenagalistrikan Kalimantan Disampaikan Pada : Skema Pembangunan Infrastruktur Ketenagalistrikan ( PIK ),” 2015.

S. Rahmat, A. G. Abdullah, and Hasbullah, “Koordinasi Hidro Thermal Unit Pembangkitan Jawa-bali menggunakan Metode Dynamic Programming,” Electrans, Vol 13 no 2, vol. 444, no. 2, pp. 167–180, 2014.

G. Yuan and W. Yang, "Study on optimization of economic dispatching of electric power system based on Hybrid Intelligent Algorithms (PSO and AFSA)," Energy, vol. 183, pp. 926–935, 2019, doi: 10.1016/j.energy.2019.07.008.

E. E. Elattar, "Environmental economic dispatch with heat optimization in the presence of renewable energy based on modified shuffle frog leaping algorithm," Energy, vol. 171, pp. 256–269, 2019, doi: 10.1016/j.energy.2019.01.010.

K. Sureshkumar and V. Ponnusamy, "Power flow management in micro grid through renewable energy sources using a hybrid modified dragonfly algorithm with bat search algorithm," Energy, vol. 181, pp. 1166–1178, 2019, doi: 10.1016/j.energy.2019.06.029.

B. Dey, S. K. Roy, and B. Bhattacharyya, "Solving multi-objective economic emission dispatch of a renewable integrated microgrid using latest bio-inspired algorithms," Eng. Sci. Technol. an Int. J., vol. 22, no. 1, pp. 55–66, 2019, doi: 10.1016/j.jestch.2018.10.001.

M. Amiri, S. Khanmohammadi, and M. A. Badamchizadeh, "Floating search space: A new idea for efficient solving the Economic and emission dispatch problem," Energy, vol. 158, pp. 564–579, 2018, doi: 10.1016/j.energy.2018.05.062.

C. Shilaja and T. Arunprasath, "Internet of medical things-load optimization of power flow based on hybrid enhanced grey wolf optimization and dragonfly algorithm," Futur. Gener. Comput. Syst., vol. 98, pp. 319–330, 2019, doi: 10.1016/j.future.2018.12.070.

L. L. Li, X. Zhao, M. L. Tseng, and R. R. Tan, "Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm," J. Clean. Prod., vol. 242, p. 118447, 2020, doi: 10.1016/j.jclepro.2019.118447.

J. Li, J. Lu, L. Yao, L. Cheng, and H. Qin, "Wind-Solar-Hydro power optimal scheduling model based on multiobjective dragonfly algorithm," Energy Procedia, vol. 158, pp. 6217–6224, 2019, doi: 10.1016/j.egypro.2019.01.476.

N. K. A. yani Bobby Prayogo, rony setyo wibowo, “Koordinasi Jangka Pendek Pembangkit Hydrothermal menggunakan Firefly algoritm,” Tek. Its, 2016.

T. T. Nguyen and D. N. Vo, "An efficient cuckoo bird inspired meta-heuristic algorithm for short-term combined economic emission hydrothermal scheduling," Ain Shams Eng. J., vol. 9, no. 4, pp. 483–497, 2018, doi: 10.1016/j.asej.2016.04.003.

H. Saadat, "Power System Analysis." McGraw-Hill, 1999.

V. K. Jadoun, N. Gupta, K. R. Niazi, and A. Swarnkar, "Modulated particle swarm optimization for economic emission dispatch," Int. J. Electr. Power Energy Syst., vol. 73, pp. 80–88, 2015, doi: 10.1016/j.ijepes.2015.04.004.

J. M. T. Haryono, “Iterasi Lambda Menggunakan Komputasi Pararel,” pp. 1–6.




DOI: http://dx.doi.org/10.25139/inform.v6i1.3320

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