Climate change, greenhouse gases, and global warming are global issues today. Of course, this global issue cannot be separated from the issue of emissions. Various methods to solve generator scheduling problems by considering emissions or Economic Emission Dispatch (EED) have been published, but not to the extent of calculating the cost to reduce emissions. The main objective of this research is to determine the cost of reducing the emission of electricity generation in Indonesia through solving the EED problem. The method proposed to solve the EED problem is an annealing simulation algorithm and tested using an electrical system of eight generators, four different loads, and five combinations of cost and emission weights. This method is tested with various loads (conditions), and each condition is tested with various combinations of cost weights and emission weights. The obtained results were compared with the results of the calculation of the Cuckoo algorithm, and the whale optimization algorithm. The simulation results show that it costs US$258.81 to reduce 1 ton of emissions. This paper can be used as a material for further consideration for the government and generator providers in making policies related to the operation of power plants by considering emissions.
Ramírez-Tovar, A., Moreno, R. and Carrillo-Rodríguez, L.A., "The colombian energy policy challenges in front of climate change", International Journal of Energy Economics and Policy, Vol. 11, No. 6, (2021), 401, doi: 10.32479/ijeep.10517.
2. Mumuh, M., Herlina, N., Falah, M., Saringendyanti, E., Sofianto, K. and Zin, N.M., "Impact of climate change on agriculture sector of malaysia", International Journal of Energy Economics and Policy, Vol. 11, No. 6, (2021), 138, doi: 10.32479/ijeep.10939.
3. Bunnag, T., "The causal relationship among CO2 emission, oil consumption and economic growth in thailand: Ardl bound testing approach", International Journal of Energy Economics and Policy, 11, No. 6, (2021), 427, doi: 10.32479/ijeep.11811.
4. Shaari, M.S., "The impacts of rural population growth, energy use and economic growth on CO2 emissions", 670216917, (2021), doi: 10.32479/ijeep.11566.
5. Mardiyanto, I.R., Zein, H. and Soeprijanto, A., "Combining parameters of fuel and greenhouse gas costs as single objective function for optimization of power flow", Telkomnika, 15, No. 4, (2017), 1585-1600, doi: 10.12928/TELKOMNIKA.v15i4.5769.
6. Fasihi, M., Tavakkoli-Moghaddam, R., Najafi, S.E. and Hajiaghaei-Keshteli, M., "Developing a bi-objective mathematical model to design the fish closed-loop supply chain", International Journal of Engineering,Transaction B: Applications, 34, No. 5, (2021), 1257-1268, doi: 10.5829/IJE.2021.34.05B.19.
7. Chouhan, V.K., Khan, S.H. and Hajiaghaei-Keshteli, M., "Sustainable planning and decision-making model for sugarcane mills considering environmental issues", Journal of Environmental Management, 303, (2022), 114252, doi: 10.1016/j.jenvman.2021.114252.
8. Mehranfar, N., Hajiaghaei-Keshteli, M. and Fathollahi-Fard, A.M., "A novel hybrid whale optimization algorithm to solve a production-distribution network problem considering carbon emissions", International Journal of Engineering, Transaction C: Aspects, 32, No. 12, (2019), 1781-1789, doi: 10.5829/ije.2019.32.12c.11.
9. Fard, A., Hajiloo, A. and Tohidi, N., "Using neural network and genetic algorithm for modeling and multi-objective optimal heat exchange through a tube bank", doi: 10.5829/idosi.ije.2012.25.04c.07.
10. Sadafi, M., Hosseini, R., Safikhani, H., Bagheri, A. and Mahmoodabadi, M., "Multi-objective optimization of solar thermal energy storage using hybrid of particle swarm optimization and multiple crossover and mutation operator", (2011), doi: 10.5829/idosi.ije.2011.24.04b.07.
11. El-Henawy, I. and Abdelmegeed, N.A., "Meta-heuristics algorithms: A survey", International Journal of Computer Applications, 179, No. 22, (2018), 45-54, doi: 10.5120/ijca2018916427.
12. Arthur, J.K., Frimpong, E.A. and Adjei, J.O., "Optimization algorithms for solving combined economic emission dispatch: A review", in Proceedings of the World Congress on Engineering and Computer Science. (2019), 22-24.
13. Gopalakrishnan, R. and Krishnan, A., "An advanced genetic optimization algorithm to solve combined economic and emission dispatch problem", Bonfring International Journal of Man Machine Interface, 2, No. 1, (2012), 11-19.
14. Radosavljević, J., "Gravitational search algorithm for solving combined economic and emission dispatch", in Proc. XIV Int. Scientific-Professional Symposium Infoteh. (2015).
15. Kahrizi, M. and Kabudian, S., "Projectiles optimization: A novel metaheuristic algorithm for global optimization", International Journal of Engineering, Transaction A: Basics, Vol. 33, 10, (2020), 1924-1938, doi: 10.5829/ije.2020.33.10a.11.
16. Yuan, G., Yang, Y., Tian, G. and Fathollahi-Fard, A.M., "Capacitated multi-objective disassembly scheduling with fuzzy processing time via a fruit fly optimization algorithm", Environmental Science and Pollution Research, (2022), 1-18, doi: 10.1007/s11356-022-18883-y.
17. Shijing, D., Hongru, C., Xudong, W., Deshi, W. and Yongyong, Z., "Modal optimization design of supporting structure based on the improved particle swarm algorithm", International Journal of Engineering, Transaction A: Basics, 35, No. 4, (2022), 740-749, doi: 10.5829/ije.2022.35.04a.14.
18. Mohammadi, S. and Babagoli, M., "A hybrid modified grasshopper optimization algorithm and genetic algorithm to detect and prevent ddos attacks", International Journal of Engineering, Transaction A: Basics, 34, No. 4, (2021), 811-824, doi: 10.5829/ije.2021.34.04a.07.
19. Shafiee, M., Amirahmadi, M., Farzinfar, M. and Lapthorn, A., "Voltage stability improvement in optimal placement of voltage regulators and capacitor banks based on fsm and mmopso approach", International Journal of Engineering, Transaction A: Basics, 34, No. 4, (2021), 881-890, doi: 10.5829/ije.2021.34.04a.14.
20. Ghaffarian, N. and Hamedi, M., "Optimization of rubber compound design process using artificial neural network and genetic algorithm", International Journal of Engineering, Transaction B: Applications, 33, No. 11, (2020), 2319-2326, doi: 10.5829/ije.2020.33.11b.22.
21. Hasibi, H., Mahmoudian, A. and Khayati, G., "Modified particle swarm optimization-artificial neural network and gene expression programing for predicting high temperature oxidation behavior of Ni–Cr–W-MO alloys", International Journal of Engineering, Transaction B: Applications, 33, No. 11, (2020), 2327-2338, doi: 10.5829/IJE.2020.33.11B.23.
22. Goodarzian, F., Hosseini-Nasab, H. and Fakhrzad, M., "A multi-objective sustainable medicine supply chain network design using a novel hybrid multi-objective metaheuristic algorithm", International Journal of Engineering, Transaction A: Basics, 33, No. 10, (2020), 1986-1995, doi: 10.5829/IJE.2020.33.10A.17.
23. Esfandian, H., Esfandian, N. and Rezazadeh, M., "Modeling and comparison of optimized isotherm models for H2, N2, CO, CH4 and CO2 adsorption using cuckoo search optimization algorithm", International Journal of Engineering, Transaction B: Applications, 33, No. 5, (2020), 712-719, doi: 10.5829/IJE.2020.33.05B.01.
24. Beiki, H., Seyedhosseini, S., Ghezavati, V. and Seyedaliakbar, S., "Multi-objective optimization of multi-vehicle relief logistics considering satisfaction levels under uncertainty", International Journal of Engineering, Transaction B: Applications, 33, No. 5, (2020), 814-824, doi: 10.5829/ije.2020.33.05b.13.
25. Chouhan, V.K., Khan, S.H. and Hajiaghaei-Keshteli, M., "Metaheuristic approaches to design and address multi-echelon sugarcane closed-loop supply chain network", Soft Computing, 25, No. 16, (2021), 11377-11404, doi: 10.1007/s00500-021-05943-7.
26. Abido, M., "Multiobjective particle swarm optimization for environmental/economic dispatch problem", Electric Power Systems Research, 79, No. 7, (2009), 1105-1113, doi: 10.1016/j.epsr.2009.02.005.
27. Xin-gang, Z., Ji, L., Jin, M. and Ying, Z., "An improved quantum particle swarm optimization algorithm for environmental economic dispatch", Expert Systems with Applications, 152, (2020), 113370, doi: 10.1016/j.eswa.2020.113370.
28. Jadoun, V.K., Gupta, N., Niazi, K. and Swarnkar, A., "Modulated particle swarm optimization for economic emission dispatch", International Journal of Electrical Power & Energy Systems, 73, (2015), 80-88, doi: 10.1016/j.ijepes.2015.04.004.
29. Maghzi, P., Mohammadi, M., Pasandideh, S. and Naderi, B., "Operating room scheduling optimization based on a fuzzy uncertainty approach and metaheuristic algorithms", International Journal of Engineering, Transaction B: Applications, 35, (2022), 275-258, doi: 10.5829/IJE.2022.35.02B.01.
30. Izadi, L., Ahmadizar, F. and Arkat, J., "A hybrid genetic algorithm for integrated production and distribution scheduling problem with outsourcing allowed", International Journal of Engineering, Transaction B: Applications, 33, No. 11, (2020), 2285-2298, doi: 10.5829/ije.2020.33.11b.19.
31. Jain, A., Porpatham, E. and Thipse, S., "Emission reduction strategies for small single cylinder diesel engine using valve timing and swirl ratio", International Journal of Engineering, Transaction B: Applications, 33, No. 8, (2020), 1608-1619, doi: 10.5829/ije.2020.33.08b.19.
32. Jeddi, B. and Vahidinasab, V., "A modified harmony search method for environmental/economic load dispatch of real-world power systems", Energy Conversion and Management, 78, (2014), 661-675, doi: 10.1016/j.enconman.2013.11.027.
33. Júnior, J.d.A.B., Nunes, M.V.A., Nascimento, M.H.R., Rodríguez, J.L.M. and Leite, J.C., "Solution to economic emission load dispatch by simulated annealing: Case study", Electrical Engineering, 100, No. 2, (2018), 749-761, doi: 10.1007/s00202-017-0544-0.
34. Eliezer, I., "Dynamic economic emission dispatch pada sistem transmisi jawa-bali 500 kv berdasarkan ruptl tahun 2015-2024 menggunakan metode multi-objective particle swarm optimization (MOPSO)", Institut Teknologi Sepuluh Nopember Surabaya (2016), .
35. Rahmatullah, A.D., "Pendekatan dengan cuckoo optimization algorithm untuk solusi permasalahan economic emission dispatch", Institut Teknologi Sepuluh Nopember (2017),
36. Ziane, I., Benhamida, F. and Graa, A., "Simulated annealing optimization for multi-objective economic dispatch solution", Leonardo Journal of Sciences, 13, No. 25, (2014), 43-56
37. Phommixay, S., Doumbia, M.L. and Lupien St-Pierre, D., "Review on the cost optimization of microgrids via particle swarm optimization", International Journal of Energy and Environmental Engineering, 11, No. 1, (2020), 73-89, doi: 10.1007/s40095-019-00332-1.
38. Daqaq, F., Ouassaid, M. and Ellaia, R., "Wind thermal economic emission dispatch solution using multi-objective backtracking search algorithm", in 2017 International Renewable and Sustainable Energy Conference (IRSEC), IEEE., (2017), 1-6.
39. Kuo, M.-T., Lu, S.-D. and Tsou, M.-C., "Considering carbon emissions in economic dispatch planning for isolated power systems: A case study of the taiwan power system", IEEE Transactions on Industry Applications, 54, No. 2, (2017), 987-997, doi: 10.1109/TIA.2017.2771338.
41. Lu, S.-D., Wang, M.-H., Kuo, M.-T., Tsou, M.-C. and Liao, R.-M., "Optimal unit commitment by considering high penetration of renewable energy and ramp rate of thermal units-a case study in taiwan", Applied Sciences, 9, No. 3, (2019), 421, doi: 10.3390/app9030421.
42. Wicaksono, B., Abdullah, A. and Saputra, W., "Coordination hydrothermal interconnection java-bali using simulated annealing", in IOP Conference Series: Materials Science and Engineering, IOP Publishing. Vol. 128, (2016), 012005.
Puspitasari, K. M. D., Raharjo, J., Sastrosubroto, A. S., & Rahmat, B. (2022). Generator Scheduling Optimization Involving Emission to Determine Emission Reduction Costs. International Journal of Engineering, 35(8), 1468-1478. doi: 10.5829/ije.2022.35.08b.02
MLA
K. M. D. Puspitasari; J. Raharjo; A. S. Sastrosubroto; B. Rahmat. "Generator Scheduling Optimization Involving Emission to Determine Emission Reduction Costs". International Journal of Engineering, 35, 8, 2022, 1468-1478. doi: 10.5829/ije.2022.35.08b.02
HARVARD
Puspitasari, K. M. D., Raharjo, J., Sastrosubroto, A. S., Rahmat, B. (2022). 'Generator Scheduling Optimization Involving Emission to Determine Emission Reduction Costs', International Journal of Engineering, 35(8), pp. 1468-1478. doi: 10.5829/ije.2022.35.08b.02
VANCOUVER
Puspitasari, K. M. D., Raharjo, J., Sastrosubroto, A. S., Rahmat, B. Generator Scheduling Optimization Involving Emission to Determine Emission Reduction Costs. International Journal of Engineering, 2022; 35(8): 1468-1478. doi: 10.5829/ije.2022.35.08b.02
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