Optimal DG allocation and sizing in power system networks using swarm-based algorithms
Kayode Adetunji, Ivan Hofsajer, Ling Cheng

TL;DR
This paper compares swarm-based algorithms, PSO and WOA, for optimal placement and sizing of distributed generation units in power networks, aiming to improve efficiency and stability while reducing costs.
Contribution
It introduces and evaluates PSO and WOA algorithms for DG placement and sizing, demonstrating their effectiveness on IEEE test systems and analyzing their relative strengths.
Findings
WOA achieved greater real power loss reduction in both test systems.
PSO resulted in smaller total DG unit sizes.
Both algorithms outperformed traditional methods in the tested scenarios.
Abstract
Distributed generation (DG) units are power generating plants that are very important to the architecture of present power system networks. The benefit of the addition of these DG units is to increase the power supply to a network. However, the installation of these DG units can cause an adverse effect if not properly allocated and/or sized. Therefore, there is a need to optimally allocate and size them to avoid cases such as voltage instability and expensive investment costs. In this paper, two swarm-based meta-heuristic algorithms, particle swarm optimization (PSO) and whale optimization algorithm (WOA) were developed to solve optimal placement and sizing of DG units in the quest for transmission network planning. A supportive technique, loss sensitivity factors (LSF) was used to identify potential buses for optimal location of DG units. The feasibility of the algorithms was confirmed…
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Taxonomy
TopicsOptimal Power Flow Distribution · Power System Optimization and Stability · Electric Power System Optimization
MethodsTest
