Abstract:
Distribution grids have received a lot of attention lately due to the increase in load demand. To
achieve the best possible technical, economic, commercial, and regulatory goals, distributed
generation (DG) planning must consider the proper location, sizing, and control of these factors
with different power grid types. This research provides an improved method for the simultaneous
optimal DG placement and size. Multi-Objective Particle Swarm Optimization (MOPSO) is
improved and proposed to find the optimal size and position of DGs, subject to equality and
inequality constraints. Furthermore, a fuzzy set theory is developed to select the best compromise
solution from the Pareto optimal set based on decision preferences. Newton-Raphson load flow
analysis is performed on IEEE 33 bus and IEEE 69 bus test systems. The proposed algorithm will
be tested on these two test systems to ensure its effectiveness and robustness. Additionally, a
comparison of the proposed technique with other multi-objective algorithms, such as conventional
MOPSO, MOCDE, and MOWOA is included. It has been discovered that the proposed technique
can deliver better outcomes in terms of reducing total active power loss, total annual economic
loss, and voltage profile improvement.
