  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 on two IEEE bus test systems
(14- and 30-bus). Comparison results showed that both algorithms produce good
solutions and they outperform each other in different metrics. The WOA real
power loss reduction considering techno-economic factors in the IEEE 14-bus and
30-bus test system are 6.14 MW and 10.77 MW, compared to the PSOs' 6.47 MW and
11.73 MW respectively. The PSO has a more reduced total DG unit size in both
bus systems with 133.45 MW and 82.44 MW compared to WOAs' 152.21 MW and 82.44
MW respectively. The paper unveils the strengths and weaknesses of the PSO and
the WOA in the application of optimal sizing of DG units in transmission
networks.
