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

Dosoglu M. K., GÜVENÇ U., Duman S., SÖNMEZ Y., KAHRAMAN H. T.

NEURAL COMPUTING & APPLICATIONS, cilt.29, sa.3, ss.721-737, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 3
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1007/s00521-016-2481-7
  • Dergi Adı: NEURAL COMPUTING & APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.721-737
  • Anahtar Kelimeler: Symbiotic organisms search, Economic emission dispatch, Valve point effect, Transmission line losses, EMISSION LOAD DISPATCH, PARTICLE SWARM OPTIMIZATION, BIOGEOGRAPHY-BASED OPTIMIZATION, ECONOMIC-DISPATCH, ENVIRONMENTAL/ECONOMIC DISPATCH, GENETIC ALGORITHM
  • Gazi Üniversitesi Adresli: Evet

Özet

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.