Performance Evaluation of HEBMO for Non-convex Economic Dispatch Problems Under Contingencies
Computer programming; Economic analysis; Electric industry; Electric power system economics; Evolutionary algorithms; Operating costs; Barnacle mating optimizer; Economic dispatch problems; Matings; Non-convex economic load dispatch; Nonconvex economic dispatches; Optimisations; Optimizers; Performa...
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-270392023-05-29T17:38:54Z Performance Evaluation of HEBMO for Non-convex Economic Dispatch Problems Under Contingencies Ismail N.L. Musirin I. Dahlan N.Y. Mansor M.H. Sentilkumar A.V. Johari D. 57190935802 8620004100 24483200900 56372667100 58068868900 24733632200 Computer programming; Economic analysis; Electric industry; Electric power system economics; Evolutionary algorithms; Operating costs; Barnacle mating optimizer; Economic dispatch problems; Matings; Non-convex economic load dispatch; Nonconvex economic dispatches; Optimisations; Optimizers; Performances evaluation; Ramp rate limits; Reliability test system; Electric load dispatching Economic dispatch study is important in the electric power industry because it is concerned with efficient electrical power production and economics. It is crucial to reduce the operating costs of electric energy because even small savings have a large impact on total generation costs and fuel consumption. This paper presents the proposed algorithm namely Hybrid Evolutionary-Barnacles Mating Optimization (HEBMO) to solve non-convex economic dispatch (ED) problems specifically under the line and generator outages. The evaluation is tested on two types of reliability test systems (RTS), named IEEE 30-Bus RTS and IEEE 57-Bus RTS. HEBMO is compared to a single optimization algorithm, EP and BMO for performance evaluation purposes. The results show that the HEBMO algorithm outperforms EP and BMO in terms of minimizing the generation cost. On the other hand, HEBMO also achieves a convincing performance in terms of fast computational time. � 2022 IEEE. Final 2023-05-29T09:38:54Z 2023-05-29T09:38:54Z 2022 Conference Paper 10.1109/PECon54459.2022.9988900 2-s2.0-85146416702 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146416702&doi=10.1109%2fPECon54459.2022.9988900&partnerID=40&md5=04b2e721b09259157c880853b988e994 https://irepository.uniten.edu.my/handle/123456789/27039 281 286 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Computer programming; Economic analysis; Electric industry; Electric power system economics; Evolutionary algorithms; Operating costs; Barnacle mating optimizer; Economic dispatch problems; Matings; Non-convex economic load dispatch; Nonconvex economic dispatches; Optimisations; Optimizers; Performances evaluation; Ramp rate limits; Reliability test system; Electric load dispatching |
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57190935802 |
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57190935802 Ismail N.L. Musirin I. Dahlan N.Y. Mansor M.H. Sentilkumar A.V. Johari D. |
| format |
Conference Paper |
| author |
Ismail N.L. Musirin I. Dahlan N.Y. Mansor M.H. Sentilkumar A.V. Johari D. |
| spellingShingle |
Ismail N.L. Musirin I. Dahlan N.Y. Mansor M.H. Sentilkumar A.V. Johari D. Performance Evaluation of HEBMO for Non-convex Economic Dispatch Problems Under Contingencies |
| author_sort |
Ismail N.L. |
| title |
Performance Evaluation of HEBMO for Non-convex Economic Dispatch Problems Under Contingencies |
| title_short |
Performance Evaluation of HEBMO for Non-convex Economic Dispatch Problems Under Contingencies |
| title_full |
Performance Evaluation of HEBMO for Non-convex Economic Dispatch Problems Under Contingencies |
| title_fullStr |
Performance Evaluation of HEBMO for Non-convex Economic Dispatch Problems Under Contingencies |
| title_full_unstemmed |
Performance Evaluation of HEBMO for Non-convex Economic Dispatch Problems Under Contingencies |
| title_sort |
performance evaluation of hebmo for non-convex economic dispatch problems under contingencies |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806427348644397056 |