This paper presents an optimal method for optimizing network reconfiguration problems in a power distribution system in order to enhance reliability and reduce power losses. Network reconfiguration can be viewed as an optimization problem involving a set of criteria that must be reduced when adhering to various constraints. The energy not supplied (ENS) during permanent network faults and active power losses are the objective functions that are optimized in this study during the reconfiguration phase. These objectives are expressed mathematically and will be integrated into various optimization algorithms used throughout the study. To begin, a mathematical formulation of the objectives to be optimized, as well as all the constraints that must be met, is proposed. Then, to solve this difficult combinatorial problem, we use the exhaustive approach, genetic algorithm (GA), and particle swarm optimization (PSO) on an IEEE 33-bus electrical distribution network. Finally, a performance evaluation of the proposed approaches is developed. The results show that optimizing the distribution network topology using the PSO approach contributed significantly to improving the reliability, node voltage, line currents, and calculation time.

This paper considers the problem of admissibility and admissibilization of 2D singular continuous systems described by the Roesser model. A necessary and sufficient admissibility condition is first proposed for 2D singular continuous systems in terms of a strict Linear Matrix Inequality (LMI). Then, a necessary and sufficient condition is established for the closed-loop system to be admissible (i.e., stable, regular, and impulse-free). Moreover, the stability condition is completed to give a sufficient condition to ensure a specified H_∞ disturbance attenuation level for the state feedback closed loop. To illustrate the effectiveness of the proposed methodology, a numerical example is given to illustrate an admissibilization of a state feedback closed-loop system.