A probabilistic analysis of islanding effects in a modeled distribution system with renewable resources

For this research, an investigation was undertaken regarding the inclusion of renewable resources into the distribution system. This incorporated the increasing prevalence of solar and wind resources, as well as the development of islanding capabilities within distribution systems. A model of an actual distribution system was modified to include both solar and wind generation at the end of a feeder, which was also given the capability of islanding. Backup generation was also added to this segment of the system to ensure the reliability of the operation of the renewable resources. This model system was investigated in two different avenues, probability analysis and transient analysis, which were then experimentally combined into a hybrid analysis. In the probability analysis, the practice of using probability density functions to describe the behavior of wind and solar phenomena was utilized in conjunction with real-world weather data. This provided a basis for this research to draw real conclusions regarding the adequacy of renewable resources for different portions of the day, as well as realistic estimations of resource contributions. Additionally, alternative methods for investigating the solar resource were analyzed to provide more a more useful approach than the more complex schemes currently being utilized. Lastly, examples of probability analysis providing more accurate understanding than basic analyses of renewable resources were demonstrated. For the transient analyses, the system model was simulated for various scenarios in the PSCAD environment. The effects of different levels of generation along with the switching operations associated with islands were explored. This provided a basis to understand some of the effects that may be anticipated by the addition of renewable resources within the distribution system. Not only was this investigated for voltage and current levels, but also for the power generation levels of the renewable resources themselves. Finally, these two distinctive areas of research were combined to experimentally provide a comprehensive view of such systems. This provided various avenues in which to present original views of the system. Among these included methods of breaking the system behavior down along lines of generation levels as well as time-of-day progression. Additionally, a means of predictive analysis was explored using the combinational methodology, with results being provided by the historic data used for the probability analysis.