Research on improvement method of distributed generation optimization configuration
Cailian Gu, Jianwei Ji, Lifen Liu, Cheng Guo
Abstract
Cailian Gu, Jianwei Ji, Lifen Liu, Cheng Guo
Abstract
The influence on distribution network of the distributed generation (DG) is closely related to the location and capacity connected to the DG, therefore it is very important to study the problems of site selection and capacity determination. The reactive power optimization is considered to improve the voltage level of power grid and reduce line losses. According to the capacity of the DG, The problem about selecting site and determining capacity is decomposed into two kinds of pattern with Parallel operation and island operation, which means comprehensive target of grid losses. voltage deviation and static voltage stability margin is optimal while DG is full load. Optimal allocation model of DG is established, the constraints condition includes node voltage, the transmission current of line, the single DG capacity and the total capacity of all DG. The genetic - ant colony hybrid intelligent algorithm is put forward to calculate the location and capacity of the DG. Simulation results show that the method is effective in problem of location selecting and capacity determing of DG.
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The influence on distribution network of the distributed generation (DG) is closely related to the location and capacity connected to the DG, therefore it is very important to study the problems of site selection and capacity determination. The reactive power optimization is considered to improve the voltage level of power grid and reduce line losses. According to the capacity of the DG, The problem about selecting site and determining capacity is decomposed into two kinds of pattern with Parallel operation and island operation, which means comprehensive target of grid losses. voltage deviation and static voltage stability margin is optimal while DG is full load. Optimal allocation model of DG is established, the constraints condition includes node voltage, the transmission current of line, the single DG capacity and the total capacity of all DG. The genetic - ant colony hybrid intelligent algorithm is put forward to calculate the location and capacity of the DG. Simulation results show that the method is effective in problem of location selecting and capacity determing of DG.
Key concepts: Distributed generation, Voltage, Genetic algorithm, Ant colony optimization algorithms, Computer science, Grid, Mathematical optimization, AC power