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<p>The electrical distribution network is a critical and complex system in terms of safety and reliability, because it is composed of different components (switches, reclosers, etc.). The improvement of its reliability is therefore one of the most important tasks through the good management of remote-controlled switches and reclosers in this network. This paper presents an analytical model based on graph theory to evaluate SAIDI and SAIFI indices based on the network architecture and the location of remote-controlled reclosers and switches. These indicators have been used to formalize a multi-objective mathematical model that respects the real operation constraints of equipments in smart grid. The applied model, in this article, was evaluated on an IEEE 13 bus network using the TOPSIS method to determine the optimal location of the switches and reclosers and to improve the overall reliability of the distribution network.</p>

<p class="Default">Nowadays, the use of the wind energy has known an important increase because it is clean and cheap. However, many technical issues could occur due to the integration of wind power plants into power grids. As a result, many countries have published grid code requirements that new installed wind turbines have to satisfy in order to facilitate its intergration to electrical networks. Among those requirements, the wind farms must be able to participate to ancillary services for instance voltage regulation and reactive power control. Nevertheless, in case of small wind farms having not the necessary reactive power capability to contribute to reactive power support, Flexible AC Transmission Systems (FACTS) devices could also be used to participate to reactive power support. In this paper, an optimization method based on particle swarm optimization (PSO) technique is presented. This method allows getting the optimal location and reactive power injection of both wind power plants (WPP) and synchronous var compensators (SVC) with the objective to improve the voltage profile and to minimize the active power losses. The IEEE 14 bus system and a 20 MW wind farm based doubly fed induction generator (DFIG) are used to validate the proposed algorithm. The simulation results are analysed and compared.</p>