Optimal Allocation and Sizing of Distributed Generation with Soft Computing Technique for Loss Reduction

Abstract

ABSTRACT newlineThe increase in electricity consumption has driven advances in the use of small and medium-sized generators connected to the distribution system in contradiction to the previous paradigm, where the generation centers are concentrated and far from the loads. Long feeders responsible for connecting the supply substations to the load centers are associated with losses inherent to the components of the electrical network. In this scenario, the use of Distributed Generation (DG) can contribute to supplying the growing demand for energy and provide improvements in important parameters in the supply of energy, such as reducing system losses and improving the adequacy of the voltage profile. newlineDG has become a complementary energy source for centralized generation, it has gained a lot of space in distribution systems. In addition, the large plants involve high costs, large greenhouse gas emissions and difficulty in obtaining environmental permits, these factors have also boosted the use of DG with renewable resources (wind, solar and water). newlineHowever, in order to guarantee the benefits of using DGs, it is necessary to carry out studies of their positioning and dimensioning. The positioning and dimensioning of DGs is a mixed integer non-linear mathematical problem, which has a set of solutions susceptible to accelerated growth as the number of bars in the system or generators increases. In the problem of optimal location and dimensioning, two objectives have been considered: the minimization of active losses and the improvement of the voltage profile. newlineOptimization methods are tools that can be utilized to locate and dimension the DG units in the system, in order to use these units within certain established limits and restrictions. In this sense, the objective of this work is to apply Shuffled Frog-Leaping Algorithm (SFLA), Firefly Algorithm, Grey Wolf Optimized Cuckoo Search Algorithm (Hybrid-method) and Whale Optimization Algorithm (WOA) for allocation and dimensioning of DGs, in order to enhance the voltage stabi