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The benefits of implementing Demand Response (DR) programs in large consumers have been widely documented. However, it is still necessary to explore in more detail the impacts of the implementation of these programs in residential users on the benefits of the distribution system operators. In this paper, we determine the effects of Demand Response (DR) on the reconfiguration of a distribution system considering the consumption characteristics of residential users in Colombia. For this purpose, the demand curve of a typical residential user was constructed for Bogotá D.C., and measurements were taken to estimate the participation of this user in a DR program. In addition, an algorithm based on Particle Swarm Optimization is used as a solution strategy for the reconfiguration problem. The results show that a distribution system reconfiguration could significantly increase the revenues obtained by a Network Operator. However, it is shown that the reduction of energy losses obtained from the DR would not provide sufficient incentives for them to promote the participation of residential users in this kind of programs. [ABSTRACT FROM AUTHOR]

Mathematical Model of a Series-Parallel (SP) photovoltaic (PV) generator represents each module through an equivalent electrical circuit denominated single diode model, this model has associated a nonlinear equation system that describes the electrical behavior of SP generator. This paper presents a solution of this system using optimization methods widely using: Trust Region Dogleg and Particle swarm optimization (PSO) for solving the electrical model of PV generator operating under homogeneous or non-homogeneous conditions, changing the number of submodules and shading pattern. It has been made simulations about generators composed by 3 and 15 series submodules, operating under different partial shading conditions. Between the implemented methods, Trust Region Dogleg show a better performance than other methods, with 2 and 14 times less computation time than the reference method and PSO, respectively, and a RMSE equal or 50% lower than PSO. [ABSTRACT FROM AUTHOR]

In this paper the particle swarm optimization (PSO) along with some of its variants is explored to give solution to the optimal reactive power dispatch problem (ORPD). This problem consists of the optimal use of reactive power resources in a power system, usually with the aim of minimizing power loses and improving voltage profile. The ORPD is a non-lineal and non-convex problem that involves continues and discrete variables and features multiple sub-optimal solutions. Besides the PSO technique, the variants known as Turbulent PSO (TPSO) and Turbulent Crazy (PSO) were implemented. Several tests were performed on IEEE 57 and 118 bus test systems comparing results with other reported in the technical literature. It was found that the performance of PSO is considerably improved when the variants TPSO and TCPSO are applied. [ABSTRACT FROM AUTHOR]

This paper analyzes the effect of different configurations of initial conditions for the optimization algorithm based on particle swarms with vorticity behavior. The proposed algorithm combines the gradient-based search and particle swarm behavior, thus, this algorithm can be affected by the initial conditions for the particles. Finally, a 2D test function is used to observe the characteristics of the algorithm. [ABSTRACT FROM AUTHOR]