Distributed generation (DG) is small generating plants which are connected to consumers in distribution systems to improve the voltage profile, voltage regulation, stability, reduction in power losses and economic benefits. The above benefits can be achieved by optimal placement of DGs. A novel nature-inspired algorithm called Dragonfly algorithm is used to determine the optimal DG units size in this paper. It has been developed based on the peculiar behavior of dragonflies in nature. This algorithm mainly focused on the dragonflies how they look for food or away from enemies. The proposed algorithm is tested on IEEE 15, 33 and 69 test systems. The results obtained by the proposed algorithm are compared with other evolutionary algorithms. When compared with other algorithms the Dragonfly algorithm gives best results. Best results are obtained from type III DG unit operating at 0.9 pf.
This paper presents a hybrid method to determine the optimal locations and sizes of DG units in distribution networks using Fuzzy and one rank cuckoo search Algorithm (ORCS). The main objective functions are to reduce total power losses and to improve voltage profiles of power distribution networks. As major power losses are occurring on distribution networks, Keen interest is evinced to reduce them. Due to the increasing interest on renewable sources in recent times, the studies on integration of distributed generation to the power grid have rapidly increased. The Distributed Generation (DG) sources are added to the networks mainly to reduce the power losses by supplying a net amount of power. In order to minimize the line losses of power systems, it is equally important to define the size and location of local generation. In this paper fuzzy approach is used to find the optimal DG locations and one rank cuckoo search algorithm is used for optimal sizes of the DG units. The proposed method is tested on IEEE 15-bus, 33-bus and 69-bus test systems and the results are presented.
This paper introduces a new Multi Objective Particle swarm Optimization algorithm (MOPSO) for the purpose of solving the DSR problem& optimal placement of DGs .The objectives of the problem are to minimize real power losses and improve the voltage profile with minimum switching operations. the best solution is determined by simply considering the sum of the normalized objective values. Radial system topology is satisfied using graph theory by formulating the branch bus incidence matrix (BBIM) and checking the rank of each topology. To test the algorithm, it was applied to widely studied test systems and a real one. The results show the efficiency of this algorithm as compared to other methods in terms of achieving all the goals simultaneously with reasonable population and generation sizes and without using a mutation rate, which is usually problem dependent.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.