文件名称:esmaeilian2015
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Different types of distributed generation (DG) are
broadly used and optimally placed in a distribution system to
improve its performance. Since the network configuration affects
the system operational conditions, the network reconfiguration
and DG placement should be manipulated simultaneously. Nevertheless, the complexity of the problem may prevent achieving
the optimal solution. This paper presents a novel hybrid method of
metaheuristic and heuristic algorithms, in order to boost robustness and shorten the computational runtime to achieve network
minimum loss configuration in the presence of DGs. -Different types of distributed generation (DG) are
broadly used and optimally placed in a distribution system to
improve its performance. Since the network configuration affects
the system operational conditions, the network reconfiguration
and DG placement should be manipulated simultaneously. Nevertheless, the complexity of the problem may prevent achieving
the optimal solution. This paper presents a novel hybrid method of
metaheuristic and heuristic algorithms, in order to boost robustness and shorten the computational runtime to achieve network
minimum loss configuration in the presence of DGs.
broadly used and optimally placed in a distribution system to
improve its performance. Since the network configuration affects
the system operational conditions, the network reconfiguration
and DG placement should be manipulated simultaneously. Nevertheless, the complexity of the problem may prevent achieving
the optimal solution. This paper presents a novel hybrid method of
metaheuristic and heuristic algorithms, in order to boost robustness and shorten the computational runtime to achieve network
minimum loss configuration in the presence of DGs. -Different types of distributed generation (DG) are
broadly used and optimally placed in a distribution system to
improve its performance. Since the network configuration affects
the system operational conditions, the network reconfiguration
and DG placement should be manipulated simultaneously. Nevertheless, the complexity of the problem may prevent achieving
the optimal solution. This paper presents a novel hybrid method of
metaheuristic and heuristic algorithms, in order to boost robustness and shorten the computational runtime to achieve network
minimum loss configuration in the presence of DGs.
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