Assessment and Optimization of Distributed Generationand Capacitor Allocation in Distribution Systems Using Artificial Intelligence Approaches

In recent years, considerable efforts have been allocated to enhance the performance of electric distribution systems. Among the most effective approaches to enhancing the performance of electric distribution systems is the installation of distributed generation (DG) and compensation capacitors, which play a critical role in reducing power losses and voltage deviations. The main objective of this study is to reduce active power losses and total voltage deviation in the system by determining the optimal locations and sizes of DG and capacitors to be installed in the distribution network. To achieve this goal, seven different scenarios were analyzed to evaluate the impact of the number of buses where DG and capacitors are installed on system performance, while keeping the total injected power constant. To solve the optimization problem, various optimization algorithms such as Artificial Bee Colony, Dragonfly, Particle Swarm Optimization (PSO), and Stochastic Fractal Search algorithms were used. These methods were tested on the standard IEEE 85-bus distribution system. The results show that allocating the total capacity of DG and capacitors to three different buses yields better results compared to locating them on a single bus or two buses. Following the placement of DG and capacitors using the aforementioned algorithms, a reduction of up to 74.1% in active power loss and up to 81.95% in voltage deviation was achieved. Although all algorithms produced similar results, the PSO algorithm generally exhibited better convergence behavior under the tested scenarios.

Cite this article as: S. Samyeli, A. Dogan and M. Alci, "Assessment and optimization of distributed generation and capacitor allocation in distribution systems using artificial intelligence approaches," Electrica, 2026, 26, 0148, doi: 10.5152/electrica.2026.25148.