چكيده به لاتين
Over the recent years, power system resilience against the severe climate events is one of the challenging issues facing electrical engineers. Since the main goal of the electric power industry is the continuity of generating energy and constant availability, it places a high premium on power systems resilience. It is very important to present a proper framework and method to evaluate the resilience of these systems because of the unique structure, special properties of electric distribution network and the increase in number and extremity of the natural events over recent years. In this regard, it seems necessary to model different capacities and properties of the smart networks components in order to provide better information about their expected performance in these cases.
In response to these challenges, this thesis addresses the concept of resilience and its dimensions in distribution networks. A single-stage model based on mixed-integer linear programming has been used for proper modeling and assessing the resilience of smart intelligence system. In the applied model, the optimum formulation of the dynamic micro grids, their service zone and optimum management of different technologies like energy storage units, demand side management programs, distributed generation units and optimal displacement of the main generation units have been investigated several times according to the given prioritization. In addition, several experiments have been conducted on the effect of employment of renewable energy resources and their uncertainty on system resilience through using a single-stage framework based on stochastic programming. The output of the integrated model employed by some simulations to the modified system IEEE-118bus and a real distribution network has been examined and verified.
Keywords: Resilience Assessment, Improvement in Electric Distribution Network Resilience, Micro Grid, Distributed Generation- Demand Response-Energy Storage System, Optimum Programming
