Parallel unbalanced three-phase power flow analysis including distributed generation models
Recently, the usage of smart grid has increased and there is a need for more efficient and comprehensive distribution system analysis tools to make proper operation and control system decisions. These requirements have given a motivation for researchers to apply innovative technologies in power syst...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/31293/5/SyafiiPFKE2011.pdf |
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| Summary: | Recently, the usage of smart grid has increased and there is a need for more efficient and comprehensive distribution system analysis tools to make proper operation and control system decisions. These requirements have given a motivation for researchers to apply innovative technologies in power system computation and modelling. This thesis presents a parallel unbalanced power flow algorithm including Distributed Generation (DG) models. DG models that have been considered are cogeneration, Photovoltaic (PV), and Wind Turbine Generator (WTG). The Radial Distribution Analysis Package (RDAP) program is used to validate the algorithm, and the performance for large-scale system is further examinedby comparing with OpenDSS software. One of the test system is a combination of a mesh network and radial feeder system that has many typical characteristics of unbalanced active systems. IEEE 8500node test system is used to test the performance of the algorithm for large unbalanced multi-phase distribution system problem. The variation of wind speed for WTG, solar radiation, and temperature for PV have been simulated. Simulation results show that the proposed DG model can be used to analyse DG impacts in unbalanced meshed and radial distribution system. The results show that the computation time of the proposed algorithm is faster than forward/backward sweep and hybrid methods. The computation time result for the 8500 test case less than 1 second showed that the proposed program is applicable to handle large-scale problems. The parallel implementation of the proposed algorithm for the combination system has improved the speedup to 2.33 times faster over the forward/backward method and have produced a computational speedup in all other cases. |
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