Maximization of generated power from wind energy conversion system using a new evolutionary algorithm
| Autor: | M.M. Sayed, E. E. Abu El-Zahab, T. A. Boghdady |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Engineering Renewable Energy Sustainability and the Environment business.industry Evolutionary algorithm PID controller 02 engineering and technology Sigmoid function Maximization Sliding mode control 020901 industrial engineering & automation Control theory Differential evolution Genetic algorithm 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business |
| Zdroj: | Renewable Energy. 99:631-646 |
| ISSN: | 0960-1481 |
| DOI: | 10.1016/j.renene.2016.07.045 |
| Popis: | In this paper, a grid-connected Doubly Fed Induction Generator controlled by a Sliding Mode Controller (SMC) is used to maximize the Wind Energy Conversion System (WECS) output power. A SMC is implemented using a PID controller that is tuned using a new algorithm based on hybrid Differential Evolution with a Linearized Biogeography-Based Optimization (LBBO-DE). Biogeography-Based Optimization (BBO) is an evolutionary optimization algorithm based on a mathematical model of organism distribution. BBO permits a recombination of the solutions features by migration. A new migration model based on the sigmoid function is proposed. An analysis of the LBBO-DE is conducted using six different models, including the sigmoid model. Their performance were tested with 23 benchmark functions. The comparison reveals that the sigmoid model has the best performance. Therefore, the LBBO-DE with a sigmoid model is used to optimize the controller parameters to maximize the WECS output power. The LBBO-DE with the sigmoid model is compared with the Tyreus-Luyben tuning method, Genetic Algorithm (GA) and Linearized BBO (LBBO). The results showed that the LBBO-DE has the best performance. The proposed algorithm is verified using an experimental setup for the maximization of the generated power from the WECS and reducing power loss. |
| Databáze: | OpenAIRE |
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