Enhancement of Voltage Profile in Power Systems by Using Genetic Algorithm

Nassar, Ibrahim A.; Omara, Mohamad A.; Abdella, Mahmoud M.

doi:10.1109/mepcon47431.2019.9007979

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…Bawa Abubakar et al in [6] focus on optimizing DG placement in a Nigerian distribution network using Genetic Algorithms, achieving a 0.4% improvement in bus voltage. In [7], Ibrahim A. Nassar et al employ Genetic Algorithms to determine optimal locations for reactive power compensators, aiming to improve both voltage profiles and power losses. In [8], Muqthiar Ali Shaik and his team introduce the Equilibrium Optimizer for DG placement and network reconfiguration, aiming for both voltage improvement and loss reduction.…”

Section: Literature Reviewmentioning

confidence: 99%

Profile Optimisation in Real Distribution Networks (Case Study Long MV Feeder)

Pipić,

Bosović,

Musić

2023

B&H Electrical Engineering

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In the dynamic field of power systems, integrating distributed generation (DG) sources like solar photovoltaic (PV) plants is crucial for enhancing reliability and fostering sustainability. However, this integration poses voltage profile management challenges in electrical grids. This study investigates voltage profile optimization in Bosnia and Herzegovina’s Gračanica network, focusing on a medium voltage feeder with 68 buses. Using DIgSILENT PowerFactory software, six scenarios with different configurations of solar plants are analyzed for their impact on voltage profiles and power losses. Results show that while DG integration offers benefits, incorrect sizing or placement can increase power losses. Optimal DG benefits are linked to specific sizes and locations. This research emphasizes the need for balancing PV generation with load demands and provides insights for optimal PV plant size and output to minimize negative impacts. These findings aid energy planners and policymakers in implementing distributed solar PV in medium voltage networks.

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Section: Literature Reviewmentioning

confidence: 99%

Profile Optimisation in Real Distribution Networks (Case Study Long MV Feeder)

Pipić,

Bosović,

Musić

2023

B&H Electrical Engineering

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“…When referring to the voltage profile, it is inevitable not to refer to voltage stability since having adequate strength implies keeping the bus voltage within limits established by regulation after the occurrence of a fault, looking for the system to have a more efficient, economic, and reliable behavior [16]. When analyzing the voltage profile, it should be taken into account that its alteration is caused by the variation of loads, changes in the structure of the network due to the presence of several faults, the performance of maintenance within the network, and the fact of presenting a difference in the generation that provides energy to the system [17].…”

Section: Voltage Profilementioning

confidence: 99%

Localization and Sizing of Distributed Generation through a Genetic Algorithm to Improve Voltage Profile Using Ecuadorian Standards

Calvachi,

Tipán,

Jaramillo

2023

Energies

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The approach proposed for the development of this research work was based on the integration of Distributed Energy Generation (DG) into an energy distribution network, improving the voltage profile by establishing an optimal location and sizing of DG power plants, for which the use of a heuristic optimization method known as Genetic Algorithm (GA), which has several restrictions to limit its operation and thus achieve an optimal solution to the planned optimization problem, was resorted to. The development of a power flow allowed having the voltage measurement in the bars of the network before incorporating DG, allowing to verify that the voltage fluctuations present an improvement after the incorporation one by one of each DG central defined by the GA. The systems in which the voltage measurement was performed, as well as the verification of its fluctuations with and without DG once the GA was used, were the IEEE systems of 9 and 14 busbars, the latter the one used to demonstrate the scalability of the GA to locate and dimension DG without considering the number of busbars in a system.

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