Application of fuzzified genetic algorithm for optimal allocation of renewable energy sources into the power system

The ever-increasing population and globalization have increased demand for power. Distributed generators (DGs) are installed in distribution networks to meet increasing load demand. Improper placement of distributed generation (DG) units in power systems not only increases power loss and voltage instability but also has a negative impact on system operation. As a result, a method for determining the best DG location and size is required. In this paper, both the fast voltage stability index and the power loss index are considered objectives. The genetic algorithm is implemented to find the optimal placement and size of DG. Another method called the fuzzified genetic algorithm is also employed to find the compromise solution for DG location and sizing when multi-objective is considered. The proposed methods are tested in IEEE-14 and IEEE-30 bus systems to reduce voltage instability and power loss by placing the DG in the best locations under various conditions, such as line outages and overload. After placing the DG, the power loss and voltage instability are reduced compared to the results obtained before. Placement of DG.