Dağıtım şebekesinin ayağa kaldırılması ve durumsal farkındalık araçlarının performansının geliştirilmesi

Electricity has a crucial role in modern life, and its absence may cause catastrophic complications. Restoration of distribution systems requires an efficient decision support mechanism as well as an accurate real-time operation. Considering the utmost importance of fast restoration of the distribution system to provide uninterrupted electricity, a decision support mechanism is required to employ an efficient analysis of the system. Therefore, it is crucial to analyze the system in a fast manner. This thesis presents a computationally efficient partitioning method using a novel numeric algorithm to detect the ring structure in order to conduct the required analyses in a fast manner. Moreover, to improve the situational awareness during the restoration, a situational awareness tool is developed. The tool uses received measurements from the energized sections to estimate the observable states and to update unreliable load/generation forecasts/profiles. The proposed tool employs three-phase Least Absolute Values (LAV) estimator with a linearized measurement function to improve the computational performance without loss of accuracy significantly. Finally, the proposed situational awareness tool uses an efficient power flow formulation based on the well-known forward/backward sweep algorithm to detect any infeasible restoration strategy.