Abstract
Wind farm micro-siting is to determine the optimal placement for the wind turbines such that the cost of energy (COE) is minimal. The problem is clearly a long-term decision one, once the micro-siting was constructed, it is extremely costly to reconfigure the layout. Long-term electricity demand forecasting is a necessity for formation of governmental energy policy. We anticipate that the two problems should be considered simultaneously to create potential benefits because they have resembling properties and close supply-and-demand relationship. This paper proposes a demand-aware micro-siting system to COE minimization. The system is a holistic integration of long-term electricity demand forecasting and optimal micro-siting. A case study in central Taiwan area is conducted to validate the feasibility of the proposed system.
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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., Chao, CH., Wu, TH., Hsu, PY. (2017). Optimal Micro-siting Planning Considering Long-Term Electricity Demand. In: Tan, Y., Takagi, H., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2017. Lecture Notes in Computer Science(), vol 10386. Springer, Cham. https://doi.org/10.1007/978-3-319-61833-3_47
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DOI: https://doi.org/10.1007/978-3-319-61833-3_47
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