Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves

被引:20
|
作者
Gil-Gonzalez, Walter [1 ]
Danilo Montoya, Oscar [1 ,2 ]
Fernando Grisales-Norena, Luis [3 ]
Perea-Moreno, Alberto-Jesus [4 ]
Hernandez-Escobedo, Quetzalcoatl [5 ]
机构
[1] Univ Tecnolog Bolivar, Lab Inteligente Energia, Km 1 Via Turbaco, Cartagena 131001, Colombia
[2] Univ Dist Francisco Jose de Caldas, Fac Ingn, Carrera 7 40B-53, Bogota 11021, DC, Colombia
[3] Inst Univ Pascual Bravo, Fac Ingn, Grp GIIEN, Campus Robledo, Medellin 050036, Colombia
[4] Univ Cordoba, Dept Fis Aplicada, CeiA3, Campus Rabanales, Cordoba 14071, Spain
[5] UNAM, Escuela Nacl Estudios Super, Campus Juriquilla, Queretaro 3001, Mexico
关键词
wind power generation; artificial neural networks; chargeability factor; reactive power capacity; wind speed and demand curves; DISTRIBUTION-SYSTEMS; DISTRIBUTION NETWORK; LOSS MINIMIZATION; OPTIMIZATION; DG; ALGORITHM; LOCATION; HYBRID;
D O I
10.3390/su12072983
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper presents an optimization model for the optimal placement and sizing of wind turbines, considering their reactive power capacity, wind speed, and demand curves. The optimization model is nonlinear and is focused on minimizing power losses in AC distribution networks. Also, paired wind turbine and power conversion systems are treated via chargeability factor eta at the peak hour. This factor represents the percentage of usage of the power conversion system in the nominal wind speed conditions, and allows to support reactive power dynamically during all periods of the day as a function of the distribution system requirements. In addition, an artificial neural network is used for short-term forecasting to deal with uncertainties in wind power generation. We assume that the number of wind power distributed generators could be from zero to three generators integrated into the system, considering unit power factors and reactive power injections to follow up the effect of reactive power compensation in the daily operation. The General Algebraic Modeling System (GAMS) is employed to solve the proposed optimization model.
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页数:20
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