Locating and capacity determination of distributed generations using none-dominated sorting genetic algorithm

One of the important concepts in distributed generation planning is to find the suitable location and nominal capacity for installing these equipment. Taking a variety of objectives has always been an issue in distributed generation planning units. Having an equivalency between these objectives necessitates the usage of new methods and approaches to optimize the objectives. Reducing the losses and improving the voltage profile with lower investment (installation and commissioning costs) are discussed as the offered objectives in this paper. To solve the above optimization problem we use the None-Dominated Sorting Genetic Algorithm (NSGA-II) algorithm. The NSGA-II Algorithm provides us a collection of optimized solutions which are passed through optimized radiance levels. The collection of solutions determines that which DG units should be installed in which location. In addition to that the optimized solutions shows the amount of production by each distributed generation unit in order to have the best possible respond in the matter of loss and having the flat voltage profile. The offered procedure let the planner to choose the best results by taking the importance of different objectives into account with dissociating different objectives and avoids the pre-judgments before making the decision. This procedure is implemented and studied on a 9 bus sample network.