Optimal Distributed Generation Location and Sizing Using Genetic Algorithms

The paper proposes a comparison between nonlinear optimization and genetic algorithms for optimal location and sizing of distributed generation in a distribution network. The objective function consists of both power losses and investment costs and the methods are tested on the IEEE 69-bus system. The study covers a comparison between the proposed approaches and shows the importance of installing the right amount of DG in the best suited location. Studies show that if the DG units are connected at non-optimal locations or have nonoptimal sizes, the system losses may increase.