Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran

Minimizing power losses in a distributed system are commonly achieved via optimal network reconfiguration. In the past, network reconfiguration research focused on planning, where the final configuration reporting the lowest power loss being the main goal. However, power losses during the switching...

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Bibliographic Details
Main Author: Ola Subhi , Waheed Badran
Format: Thesis
Published: 2018
Subjects:
Online Access:http://studentsrepo.um.edu.my/9343/1/Ola_Subhi_Waheed_Badran.pdf
http://studentsrepo.um.edu.my/9343/6/ola.pdf
http://studentsrepo.um.edu.my/9343/
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Summary:Minimizing power losses in a distributed system are commonly achieved via optimal network reconfiguration. In the past, network reconfiguration research focused on planning, where the final configuration reporting the lowest power loss being the main goal. However, power losses during the switching operations from the initial state to the final state of configuration was never studied. This research presents the optimal switching sequence path to minimize power losses during the network switching operation. Apart from this contribution, simultaneous optimal network reconfiguration and optimal distributed generation (DG) output generation were also proposed. The proposed methodology involves (1) Optimal network reconfiguration and DG output simultaneously, (2) Optimal network reconfiguration with variable load and the different types of DGs and (3) Optimal sequence of switching operations required to convert the network from the original configuration to the optimal configuration obtained from (1) for both planning and operational mode. The proposed method is applied to reduce power losses and improve the overall voltage profile of the system. The proposed network reconfiguration also considered load profiles, DG output generation, DG types, and DG operating mode to decrease the total daily power loss. The chosen optimization techniques in this work include evolutionary programming (EP), particle swarm optimization (PSO), gravitational Search Algorithm (GSA), and firefly algorithm (FA). To assess the capabilities of the proposed method, simulations using MATLAB were carried out on IEEE 16-bus, IEEE 33-bus, IEEE 69-bus, and IEEE 118-bus radial distribution networks. The obtained results demonstrate the effectiveness of the proposed strategy to determine the sequence path of switching operations, as well as the optimal network configuration and optimal generation output of DG units. The optimal network reconfiguration with optimal DGs output reported high power loss reduction of (23.63%-82.233%) for different test systems. These values exceeded the values reported by other works. The proposed method also produced better voltage profile compared to other published works. The minimum value of the buses voltages was between (0.9502 p.u.-0.98176 p.u.) for different systems. The power losses during optimal switching sequence process were between (365.52kW-9265.5kW) for different systems. These values were much lower compared to any other random case. Furthermore, the optimal sequence keeps the buses voltages within allowable limit during the switching process. Meanwhile, random switching caused voltage violation during the switching process. The daily solution of the network considering load profiles and DG operating mode and type, obtained total daily power losses of 747.76kWh compare to 915.65kWh reported by other works. The proposed method also produced voltage profile within allowable limits. The minimum value of the buses voltages was between (0.985 p.u.-0.989 p.u.) during 24hr. The energy losses during the switching sequence process when considering DG operating mode and type and when the load profile was average, was 465.66 kWh compared to (543.8kWh-586.4kWh) for the different random case. Moreover, the voltage profile during the switching sequence process was within the allowable limit.