Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method
There are numerous advantages that can be obtained when Distributed Generation (DG) is integrated into the distribution systems. These advantages include improving the voltage profiles and reducing the power losses of the distribution system. Such advantages can be accomplished and confirmed if t...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/67086/1/FK%202016%20126%20IR.pdf |
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| Summary: | There are numerous advantages that can be obtained when Distributed
Generation (DG) is integrated into the distribution systems. These advantages
include improving the voltage profiles and reducing the power losses of the
distribution system. Such advantages can be accomplished and confirmed if the
DG units are optimally located and sized in the distribution systems. In fact, there
are several algorithms used for optimizing the size and finding the best location
to install DG units in the power system. Some existing algorithms need to be
improved while others, need to add a new parameter for improving the
performance of optimization methods and making it more effective and efficient.
This research aimed to reduce both total real and reactive power losses and
improve voltage profiles of the distribution system by proposing a differential
evolution (DE) algorithm to optimize DG size and location by taking into
consideration different types of DG units. The multi-objective function, which
represents the summation of product five indices by corresponding weights, was
utilized to identify the candidate buses to reduce the search space of the
algorithm. The suggested algorithm of DE was tested using IEEE 30 bus test
system and IEEE 57 bus test system taking into consideration three types of DG
units. The results obtained by using the DE method were compared with those
obtained by genetic algorithm (GA) method. It was observed that the DE method
gives a better result in terms of improving the voltage profile and reducing real
and reactive power losses compared to GA method. In the IEEE 30 bus test
system, the percentages of reduction in the real power losses obtained by the
DE method were 20.58 %, 22.08 % and 20.40 % compared with 15.03 %, 16.81
% and 19.66 % obtained by the GA method for type 1, type 2 and type 3
respectively, while the percentages of reduction in the reactive power losses
were 23.28 %, 19.20 % and 23.14 % by using the DE method compared with
17.01 %, 14.41 % and 22.49 % by using the GA method for type 1, type 2 and
type 3 respectively. The voltage profile of the system also improved after
optimizing DG sizes and locations using the DE method. However, in the IEEE 57 bus test system, the percentages of reduction in the real power losses were
17.08 %, 21.53 % and 20.20 % by DE method compared with 16.72 %, 15.91 %
and 16.86 % by the GA method for type 1, type 2 and type 3, while the
percentages of reduction in the reactive power loss were 9.64 %, 11.67 % and
9.42 % by DE method compared with 9.32 %, 10.81 % and 9.08 % by the GA
method for three types of DG units respectively. |
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