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AuthorTahir, M.W.
AuthorTahir, Muhammad Waleed
AuthorAbbas, Ghulam
AuthorIlyas, Muhammad Arsalan
AuthorUllah, Nasim
AuthorMuyeen, S. M.
Available date2023-02-27T08:30:24Z
Publication Date2022-01-01
Publication NameIEEE Access
Identifierhttp://dx.doi.org/10.1109/ACCESS.2022.3194012
CitationTahir, M. W., Abbas, G., Ilyas, M. A., Ullah, N., & Muyeen, S. M. (2022). Economic Emission and Energy Scheduling for Renewable Rich Network Using Bio-Inspired Optimization. IEEE Access, 10, 79713-79729.‏
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85135740395&origin=inward
URIhttp://hdl.handle.net/10576/40453
AbstractThis paper deals with the combined economic emission load dispatch (CEELD) problem with and without the integration of renewable energy sources (RESs), in some more rational test scenarios of single CEELD and multi-objective CEELD (MO-CEELD) optimization. Hence, an efficient and coherent approach is presented to minimize the generation and emission cost using one of the bio-inspired metaheuristic algorithms named flower pollination algorithm (FPA). The evolution of a power system along with the integration of RESs demands equal advancement in the operation and control algorithms of the power grid. Therefore, the proposed approach in this paper offers an evolutionary single and multi-objective optimization process based on a bio-inspired FPA. Further, it has been validated by achieving the best compromise solution (BCS) using the Pareto categorizing process and fuzzy membership function. Moreover, different study cases comprising eleven and fifteen thermal units with and without considering RESs are tested with the proposed technique. Finally, the effectiveness of the proposed approach is tested by comparing the simulation results with some already existing techniques in terms of overall fuel and emission cost. Significantly, it has been noticed from the results that it outperforms all the previously presented approaches like PSO, DE, GSA, AEO, BA, and dBA, thus justifying its applicability.
SponsorThe publication of this article was funded by Qatar National Library. This work was also supported by Taif University, Taif, Saudi Arabia, under Taif University Researchers Supporting Project TURSP-2020/144.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectCombined economic emission dispatch
fuzzy membership function
multi-objective flower pollination algorithm
Pareto categorizing process
price penalty factor approach
TitleEconomic Emission and Energy Scheduling for Renewable Rich Network Using Bio-Inspired Optimization
TypeArticle
Pagination79713-79729
Volume Number10
dc.accessType Open Access


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