Optimal Micro-siting Planning Considering Long-Term Electricity Demand

被引:0
|
作者
Yin, Peng-Yeng [1 ]
Chao, Ching-Hui [1 ]
Wu, Tsai-Hung [1 ]
Hsu, Ping-Yi [1 ]
机构
[1] Natl Chi Nan Univ, Nantou, Taiwan
关键词
Micro-siting; Demand forecasting; Regression; Optimization; GENETIC ALGORITHM; ENERGY DEMAND; OPTIMIZATION; TURKEY;
D O I
10.1007/978-3-319-61833-3_47
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:445 / 453
页数:9
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