Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems
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...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/24120/1/Optimal%20Location%20And%20Sizing%20Of%20Distrubuted%20Generator%20Using%20PSO%20And%20GA%20Algorithms%20In%20Power%20Systems%20-%20Ayat%20Saleh%20Hassan%20-%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/24120/2/Optimal%20Location%20And%20Sizing%20Of%20Distrubuted%20Generator%20Using%20PSO%20And%20GA%20Algorithms%20In%20Power%20Systems.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 total power losses and improve voltage profiles of the distribution system by proposing a practical swarm optimizion algorithm GA genetic algorithm to optimize DG size and location by taking into consideration increase number of DG units in the system. The multi-objective function, which represents the summation of product three indices by corresponding weights was utilized to identify the candidate buses to reduce the search space of the algorithm. The suggested algorithm of PSO and GA were tested using IEEE 30 bus test system taking into consideration with the increased number of DGs . After evaluating the robustness and efficiency of the algorithms in finding minimum power losses value, the results showed that the power losses value by PSO is lower than GA and PSO which gave the smallest standard deviation value compared to the GA algorithm and after finding the average time for each algorithm in which it can be said that the PSO is faster than the GA algorithms. |
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