Multi-Objective Coordinated Optimal Allocation of Distributed Generation and D-STATCOM in Electrical Distribution Networks Using Ebola Optimization Search Algorithm

Nowadays, reducing losses in electricity distribution networks is very important. On the other hand, the use of distributed generation sources (DGs) in distribution networks is increasing significantly. Therefore, these resources can play an essential role in reducing the power losses of distribution networks by choosing the right location and size. Along with DGs, D-FACTS tools such as D-STATCOM in distribution networks can play an influential role in reducing losses and compensating reactive power. The proposed article delves into how to coordinate best the allocation (size and placement) of DGs and D-STATCOM in a radial distribution network. The suggested technique aims to decrease active power losses, enhance the voltage profile and stability, and lower the overall cost. This optimization issue has been solved with the help of the Ebola Optimization Search Algorithm (EOSA). The proposed method for analysis is applied to IEEE 69 bus standard. The results are compared with two genetic algorithms (GA) and Particle Swarm Optimization (PSO) to investigate the ability to propose the results. The simulation findings show that the network losses can be greatly decreased, and the voltage profile can be significantly improved by strategically placing and sizing DGs and D-STATCOM.