Optimal Multi-objective Number, Locating, and Sizing of Distributed Generations and Distributed Static Compensators Considering Loadability using the Genetic Algorithm

Due to the development of distribution systems and an increase in electricity demand, and to overcome the shortcomings of distribution systems, such as high loss and low loadability, the use of distributed generations and flexible AC transmission systems devices, such as distributed static compensators, has been increased. The number, place, and capacity of these devices are significant factors affecting network loss reduction, influencing investment costs, and improving network performance. In this article, a new multi-objective function is proposed and optimized based on the genetic algorithm. The multi-objective function includes system loadability, and total costs include investment costs of distributed generations and distributed static compensators and network loss. The proposed method is applied to the IEEE 33-bus and 69-bus test systems. According to the simulation results, the total costs and system loadability have conflict with each other, and one can select each Pareto front point as an optimal point depending on the priority of system loadability or total cost.