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Distributed generations (DGs) play an important role in distribution networks. Among many of its merits, the loss and reduction of THD and the improvement of the voltage profile may be the most outstanding DG specifications. Studies show that non-optimal locations and non-optimal DG unit sizes can lead to increased losses, along with a negative effect on voltage profile and harmonics. Therefore, this work aims to determine the optimal DG distribution and size. For this, the heuristic optimization technique called Particle Swarm Optimization (PSO) is used as a resolution tool to simultaneously minimize the economic cost of the global system by changing the seated position and variable DG sizes. In this optimization method, the investment cost of the DGs and the power losses are considered to be minimized. First, a radial distribution power (PF) algorithm is run to find the optimal overall solution. Then, with respect to voltage profile, THD and loss reduction and using sensitivity analysis, PSO is used to calculate the objective function and to verify the bus voltage limits. To include the presence of harmonics, PSO was integrated with a harmonic power flow (HPF) algorithm. The proposed approach (PSO-HPF) is tested in an IEEE 15-bus radial distribution system. Finally, the return of the investment cost is calculated to show the economic justification of the DG's placement. These scenarios produce efficiency in the improvement of the voltage profile and reduction of THD and losses of power; It also allows an increase in power transfer capacity and maximum load.
The integration of distributed generation units (DGs) into energy distribution networks has become increasingly important in recent years. The objective of the optimal positioning of DG (ODGP) is to provide the best locations and sizes of the DGs to optimize the operation and planning of the electrical distribution network taking into account the capacity constraints of the DG. Several models and methods have been suggested for the solution of the ODGP problem.