Bare Bones Teaching Learning-Based Optimization Technique for Economic Emission Load Dispatch Problem Considering Transmission Losses
| Autor: | Sumit Banerjee, Chandan Kumar Chanda, Deblina Maity |
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| Rok vydání: | 2018 |
| Předmět: |
Mathematical optimization
Computer Networks and Communications Computer science 020209 energy Energy Engineering and Power Technology 02 engineering and technology Interactive Learning Electric power system Transmission (telecommunications) Signal Processing 0202 electrical engineering electronic engineering information engineering Cost analysis 020201 artificial intelligence & image processing Point (geometry) Computer Vision and Pattern Recognition Electrical and Electronic Engineering Teaching learning |
| Zdroj: | Iranian Journal of Science and Technology, Transactions of Electrical Engineering. 43:77-90 |
| ISSN: | 2364-1827 2228-6179 |
| DOI: | 10.1007/s40998-018-0158-1 |
| Popis: | Economic emission load dispatch plays a great role in power system cost analysis. The purpose of economic emission load dispatch is to minimize the fuel and emission cost satisfying load demand. Various iterative techniques had been used to solve economic emission load dispatch problem in previous years by different authors. In this article, the new teaching learning-based optimization (TLBO) technique using variant bare bones TLBO has been proposed for solving economic emission load dispatch problem with convex and non-convex constraints by considering transmission losses and valve point loading effects. Conventional TLBO has two phases like teacher phase and learner phase. In teacher phase, learners update their knowledge through sharing knowledge with teacher, and finally, learners improve their knowledge by interactions among learners. Bare bones TLBO employs an interactive learning strategy, which is the hybridization of the learning strategy in the conventional TLBO. The proposed algorithm has been applied on six-, ten- and forty-unit systems, and the results obtained are compared with existing techniques; hence, superiority of the proposed algorithm is proved. |
| Databáze: | OpenAIRE |
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