A hybrid JAYA-SMA for demand side management based dynamic economic emission dispatch
Issued Date
2023-01-01
Resource Type
Scopus ID
2-s2.0-85178092996
Journal Title
Proceedings of 2023 IEEE 2nd International Conference on Industrial Electronics: Developments and Applications, ICIDeA 2023
Start Page
528
End Page
533
Rights Holder(s)
SCOPUS
Bibliographic Citation
Proceedings of 2023 IEEE 2nd International Conference on Industrial Electronics: Developments and Applications, ICIDeA 2023 (2023) , 528-533
Suggested Citation
Dey B., Jadav R., Saha A., Dey P. A hybrid JAYA-SMA for demand side management based dynamic economic emission dispatch. Proceedings of 2023 IEEE 2nd International Conference on Industrial Electronics: Developments and Applications, ICIDeA 2023 (2023) , 528-533. 533. doi:10.1109/ICIDeA59866.2023.10295212 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/91349
Title
A hybrid JAYA-SMA for demand side management based dynamic economic emission dispatch
Author's Affiliation
Other Contributor(s)
Abstract
When fossil fuel-powered generators produce electricity, toxic substances are emitted into the atmosphere. Power engineers have a duty to establish a compromise that would reduce dangerous gas emissions when electricity is produced profitably in addition to promoting the usage of Renewable Energy Sources (RES). Among the different combined economic emission dispatch (CEED) strategies available to solve this problem, a numerical approach termed as fractional programming (FP) method was used and compared with price penalty factor (PPF) method. The dispatchable loads are modelled using a technique known as demand side management (DSM). To reduce the cost of generation without ever reducing demand, it restructures the load demand profile. The Slime Mould Algorithm (SMA) was hybridized with JAYA and it is used in this research to achieve a balance between least generation cost and pollutants both with and without the involvement of Demand Side Management (DSM). Generation cost was minimized to 78032 using JAYA algorithm. This value was further reduced to 76757 using JAYA-SMA algorithm. Numerical data also suggest that the combined use of DSM and JAYA-SMA is superior to several commonly used algorithms in tackling dynamic economic emission dispatch problems.