The Gravitational Search Algorithm (GSA) is a novel optimization method based on the law of gravity and mass interactions. It has good ability to search for the global optimum, but its searching speed is really slow in the last iterations. So the hybridization of Particle Swarm Optimization (PSO) and GSA can resolve the aforementioned problem. In this paper, a modified PSO, which the movement of particles is also based on getting away from individual worst solution other than going toward the best ones, is combined with GSA, named (PSOGSA) and is applied on ELD problem. A 6 unit case study considering transmission loss, prohibited zones and ramp rate limits and also a 40 unit system with valve point loading effect has been used to show the feasibility of the method. The results show fast and great convergence compared to the many other previously applied methods. پرونده مقاله

Distributed generation (DG) sources are becoming more prominent in distribution systems due to the incremental demands for electrical energy. Locations and capacities of DG sources have great impacts on the system losses in a distribution network. This paper presents a study aimed for optimally determining the size and location of distributed generation units in distribution systems with different load models. The objective is to minimize network power losses. The impacts of DG model on locating and sizing of DG are also presented considering different voltage dependent load models. Also, different types of customers such as industrial, residential, and commercial loads are considered for load modeling. The optimization problem has been solved using genetic algorithm. For simulation purpose, this algorithm has been executed on 33-bus and 69-bus test systems. Results show that type of DG modeling and load modeling has considerable effect on determination of the optimum siting and sizing of DGs. Also, DGs installation in optimum size and location has considerable effect on loss reduction and voltage improvement of distribution system. پرونده مقاله