Solution of Economically Load Scheduling Problem using Teaching Learning and Bio-Geography Based Hybrid Optimization Algorithm
Deblina Maity1, Sumit Banerjee2, Chandan Kumar Chanda3
1Deblina Maity*, EE department, Netaji Subhash Engineering College, Kolkata, India.
2Sumit Banerjee, EE department, Dr. B. C. Roy Engineering College, Durgapur, India.
3Chandan Kumar Chanda, EE department, Indian Institute of Engineering Science & Technology, Howrah, India.
Manuscript received on 06 August 2019. | Revised Manuscript received on 12 August 2019. | Manuscript published on 30 September 2019. | PP: 4284-4293 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5169098319/2019©BEIESP | DOI: 10.35940/ijrte.C5169.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: TThe article presents a new optimization algorithm view namely hybridization of teaching learning (TLBO) and biogeography based (BBO) optimization algorithm used to solve the convex economic dispatch (ED) problem with non-linear constraints like ramp rate limit, valve point loading effect etc. Hybridization of TLBO and BBO is the mixed combination of superior properties of TLBO and BBO. Teaching learning algorithm (TLBO) is based on teacher learner relationship in class and bio-geography algorithm (BBO) is based on geographical representation of biological species. The main goal of ED is to allocate power allocation economically meeting load demand. The proposed algorithm is tested for 13-unit, 15-unit, 40-unit and 140 unit systems. For proving superiority properties of proposed algorithm, obtained result are compared with recent algorithm. It gives optimum fuel cost compared to other optimization algorithm.
Keywords: Economic Dispatch; Algorithm based on Biogeography; Uneven Power Generation; Forbidden Operating Zone.
Scope of the Article: Bio-Science and Bio-Technology