Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests
ABSTRACTThis paper proposes a new metahaeuristic algorithm named particle swarm optimization and chaotic gravitational search algorithm (PSO-CGSA) for solving the combined economic and emission dispatch (CEED) problem. First, we determine the efficiency and effectiveness measures of the algorithm an...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | https://www.tandfonline.com/doi/10.1080/08839514.2024.2322335 |
| _version_ | 1797272194843148288 |
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| author | Milena Gajić Sanela Arsić Jordan Radosavljević Miroljub Jevtić Bojan Perović Dardan Klimenta Miloš Milovanović |
| author_facet | Milena Gajić Sanela Arsić Jordan Radosavljević Miroljub Jevtić Bojan Perović Dardan Klimenta Miloš Milovanović |
| author_sort | Milena Gajić |
| collection | DOAJ |
| description | ABSTRACTThis paper proposes a new metahaeuristic algorithm named particle swarm optimization and chaotic gravitational search algorithm (PSO-CGSA) for solving the combined economic and emission dispatch (CEED) problem. First, we determine the efficiency and effectiveness measures of the algorithm and compare it with other well-known algorithms. Then, we analyze the obtained solutions using the statistical procedure proposed in the paper. The proposed procedure contains the following: (i) the behavior analysis of the algorithms when solving the CEED problem, using non-parametric tests, and (ii) the ranking of the algorithms using the PROMETHEE/GAIA multi-criteria decision-making method. The behavior analysis is performed for two cases: (i) when solving individual variants of the CEED problem (single-problem analysis) and (ii) when solving a set of CEED variants (multiple-problem analysis). The results of the applied procedure for the test system with six generators show that PSO-CGSA has (i) the best solution for each tested variant of the CEED problem; (ii) the best standard deviation, mean value, error rate, and behavior for the CEED variant with a bi-objective function that simultaneously minimizes fuel cost and emission, taking into account the valve point effect; and (iii) the best rank when solving a set of CEED variants. |
| first_indexed | 2024-03-07T14:24:53Z |
| format | Article |
| id | doaj.art-10c78a802cda4c21bf3c82d70ebda734 |
| institution | Directory Open Access Journal |
| issn | 0883-9514 1087-6545 |
| language | English |
| last_indexed | 2024-03-07T14:24:53Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Applied Artificial Intelligence |
| spelling | doaj.art-10c78a802cda4c21bf3c82d70ebda7342024-03-06T08:10:27ZengTaylor & Francis GroupApplied Artificial Intelligence0883-95141087-65452024-12-0138110.1080/08839514.2024.2322335Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric TestsMilena Gajić0Sanela Arsić1Jordan Radosavljević2Miroljub Jevtić3Bojan Perović4Dardan Klimenta5Miloš Milovanović6Technical Faculty in Bor, University of Belgrade, Bor, SerbiaTechnical Faculty in Bor, University of Belgrade, Bor, SerbiaFaculty of Technical Sciences, University of Priština in Kosovska Mitrovica, Kosovska Mitrovica, SerbiaFaculty of Technical Sciences, University of Priština in Kosovska Mitrovica, Kosovska Mitrovica, SerbiaFaculty of Technical Sciences, University of Priština in Kosovska Mitrovica, Kosovska Mitrovica, SerbiaFaculty of Technical Sciences, University of Priština in Kosovska Mitrovica, Kosovska Mitrovica, SerbiaFaculty of Technical Sciences, University of Priština in Kosovska Mitrovica, Kosovska Mitrovica, SerbiaABSTRACTThis paper proposes a new metahaeuristic algorithm named particle swarm optimization and chaotic gravitational search algorithm (PSO-CGSA) for solving the combined economic and emission dispatch (CEED) problem. First, we determine the efficiency and effectiveness measures of the algorithm and compare it with other well-known algorithms. Then, we analyze the obtained solutions using the statistical procedure proposed in the paper. The proposed procedure contains the following: (i) the behavior analysis of the algorithms when solving the CEED problem, using non-parametric tests, and (ii) the ranking of the algorithms using the PROMETHEE/GAIA multi-criteria decision-making method. The behavior analysis is performed for two cases: (i) when solving individual variants of the CEED problem (single-problem analysis) and (ii) when solving a set of CEED variants (multiple-problem analysis). The results of the applied procedure for the test system with six generators show that PSO-CGSA has (i) the best solution for each tested variant of the CEED problem; (ii) the best standard deviation, mean value, error rate, and behavior for the CEED variant with a bi-objective function that simultaneously minimizes fuel cost and emission, taking into account the valve point effect; and (iii) the best rank when solving a set of CEED variants.https://www.tandfonline.com/doi/10.1080/08839514.2024.2322335 |
| spellingShingle | Milena Gajić Sanela Arsić Jordan Radosavljević Miroljub Jevtić Bojan Perović Dardan Klimenta Miloš Milovanović Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests Applied Artificial Intelligence |
| title | Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests |
| title_full | Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests |
| title_fullStr | Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests |
| title_full_unstemmed | Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests |
| title_short | Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests |
| title_sort | behavior analysis of the new pso cgsa algorithm in solving the combined economic emission dispatch using non parametric tests |
| url | https://www.tandfonline.com/doi/10.1080/08839514.2024.2322335 |
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