چكيده به لاتين
In recent years, smart grid is proposed as a vision to overcome the problems faced in current grids in terms of costs, losses, reliability and environmental pollution. Given the defined requirements and the horizons depicted in the context of the smart grids reliability, they are expected to be self-healing grids. Therefore, after the occurrence of a fault, the faulted sections of the network should be located and isolated as soon as possible to minimize the customers’ service interruption. By estimating the accurate location of faults, a fault locator will help to realize the self-healing concept of smart grids. Consequently, it will considerably decrease customers’ service restoration time and will improve the grid reliability.
In this thesis, considering the horizon depicted in the context of the smart grids self-healing and outage management mechanism, first, the requirements for a smart grid fault locator are defined. Then, the methods proposed in the literature for fault location in active distribution networks are all reviewed and compared in terms of their required measurement infrastructures and their applicability to smart grids. Most of the distribution system outages have their roots in medium voltage networks short-circuit faults. Therefore, considering the limitations of the previously proposed methods, two new methods are proposed in this thesis to locate short-circuit faults in medium voltage smart grids. The first method is a new impedance-based fault locator which, despite the previously proposed ones, can be performed in networks with non-synchronized measurement infrastructures. The second method is a state estimation-based method as the first method which is able to reduce the adverse effect of measurement and load data errors, utilizing all the available measurements and data in an optimal way. Both methods present accurate estimations and are applicable to smart grids with different kinds of distributed generators. Such methods are able to realize an automatic and fast restoration mechanism for smart grids.
