Generator Scheduling Optimization Involving Emission to Determine Emission Reduction Costs

被引:2
作者
Puspitasari, K. M. D. [1 ]
Raharjo, J. [1 ]
Sastrosubroto, A. S. [1 ]
Rahmat, B. [1 ]
机构
[1] Telkom Univ, Sch Elect Engn, Bandung, Indonesia
来源
INTERNATIONAL JOURNAL OF ENGINEERING | 2022年 / 35卷 / 08期
关键词
Generator Scheduling; Emission Costs; Simulated Annealing; !text type='Java']Java[!/text]-Bali Power System; PARTICLE SWARM OPTIMIZATION; ARTIFICIAL NEURAL-NETWORK; GENETIC ALGORITHM; LOAD DISPATCH; DESIGN;
D O I
10.5829/ije.2022.35.08b.02
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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 w eights 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.
引用
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页码:1 / 11
页数:11
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