An Intelligent Islanding Selection Algorithm For Optimizing the Distribution Network Based on Emergency Classification

Smart islanding in outage context is one of smart grid advantages based on integration of distributed generations and evolution of communication infrastructure. Outages are caused in major cases by weather and affect an important population in the word. Renewable resource can be a solution to supply demands in islanded region and can have the role of main utility duration outage period. This paper present an efficient power management and a smart dynamic distribution network based on some decisive parameters like geographic position, uninterrupted loads, interrupted load and classification of entities that depends on the priority, like hospitals that need continuously electricity to save people's lives. The best way to have a smart distribution system is to break the grid into clusters or micro grids. In our approach we start with searching an independent layered trees based on parameters and we define some selection concept to define covered entities and some optimization strategy to decrease number of islanded micro grids. All information are collected from sensors/meters and transmitted to the regional data center for analyzing and making decision. Decisions are executed by controllers and switchers installed in each entity. We present in this paper the approach steps based on an IEEE43 bus model. A simulation is done with some hypothesis to describe more the concept with a discussion of the distribution model simulation results. The Objective is to propose a solution to power shortages problem and define a strategy to operate in an intentional-islanding context to improve public access to power and provide consumer power during emergencies and grid outage.