Abstract
The ascending of quantity of CO2 emissions is the main factor contributing the global warming which results in extremely abnormal weather and causes disaster damages. Due to intensive CO2 pollutants produced by classic energy sources such as fossil fuels, practitioners and researchers pay increasing attentions on the renewable energy production such as wind power. Optimal wind turbine placement problem is to find the optimal number and placement location of wind turbines in a wind farm against the wake effect. The efficiency of wind power production does not necessarily grows with an increasing number of installed wind turbines. This paper presents a hyper-heuristic framework combining several lower-level heuristics with an artificial bee colony algorithm and a simulated annealing technique to construct an optimal wind turbine placement considering wake effect influence. Finally, we compare our approach with existing works in the literature. The experimental results show that our approach produces the wind power with a lower cost of energy.
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Acknowledgments
This research is partially supported by Ministry of Science and Technology of ROC, under Grant MOST 105-2410-H-260-018 -MY2.
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Yin, PY., Li, GS. (2018). A Hyper-Heuristic of Artificial Bee Colony and Simulated Annealing for Optimal Wind Turbine Placement. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10941. Springer, Cham. https://doi.org/10.1007/978-3-319-93815-8_15
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DOI: https://doi.org/10.1007/978-3-319-93815-8_15
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