Symbiotic organisms search optimization algorithm for economic/emission dispatch problem in power systems

• Published in: Neural computing & applications Vol. 29; no. 3; pp. 721 - 737
• Main Authors: Kenan Dosoglu, M., Guvenc, Ugur, Duman, Serhat, Sonmez, Yusuf, Tolga Kahraman, H.
• Format: Journal Article
• Language: English
• Published: London Springer London 01.02.2018; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Electrical loads; Emissions; Image Processing and Computer Vision; Optimization; Original Article; Power dispatch; Probability and Statistics in Computer Science; Transmission line losses; Economic emission dispatch; Valve point effect; Symbiotic organisms search
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-016-2481-7

This paper presents symbiotic organisms search (SOS) algorithm to solve economic emission load dispatch (EELD) problem for thermal generators in power systems. The basic objective of the EELD is to minimize both minimum operating costs and emission levels, while satisfying the load demand and all equality–inequality constraints. In other research direction, this multi-objective problem is converted into single-objective function by using price penalty factor approach in order to solve it with SOS. The proposed algorithm has been implemented on various test cases, with different constraints and various cost curve nature. In order to see the effectiveness of the proposed algorithm, its results are compared to those reported in the recent literature. The results of the algorithms indicate that SOS gives good results in both systems and very competitive with the state of the art for the solution of the EELD problems.