Abstract
This paper proposes an improved Cuckoo search algorithm to solve optimal power flow problems in electric power system. The proposed Self-learning Cuckoo search algorithm enhances the performance of Cuckoo eggs by employing the learner phase of Teaching-learning-based optimization. The learner phase leads Cuckoo eggs to follow better solutions. The proposed method has been applied for solving optimal power flow problems on the standard IEEE 30-bus and 57-bus systems to investigate its effectiveness. The objective of the optimal power flow problem is to minimize the total fuel cost while satisfying generator operational constraints of generators, transformers, shunt capacitors and capacity of transmission lines. The results indicate that the proposed method gives better solutions than the conventional Cuckoo search algorithm and other algorithms in literature.
| Original language | English |
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| Title of host publication | 2016 IEEE International Conference on Power System Technology, POWERCON 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781467388481 |
| DOIs | |
| Publication status | Published - 2016 Nov 22 |
| Event | 2016 IEEE International Conference on Power System Technology, POWERCON 2016 - Wollongong, Australia Duration: 2016 Sept 28 → 2016 Oct 1 |
Other
| Other | 2016 IEEE International Conference on Power System Technology, POWERCON 2016 |
|---|---|
| Country/Territory | Australia |
| City | Wollongong |
| Period | 16/9/28 → 16/10/1 |
Keywords
- Cuckoo Search Algorithm
- load change tap setting
- Optimal power flow
- shunt capacitors
- voltage profile
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
- Energy Engineering and Power Technology