Intelligent control algorithms for optimal reconfiguration of microgrid distribution system

The distribution power system in ship is very similar to a microgrid and supplies energy to navigation and operation system as well as sophisticated systems of weapons and communications. After a fault is encountered, reconfiguration refers to changing the topology of the microgrid distribution network in order to isolate system damage and/or optimize certain characteristics of the system. Reconfiguration problem in microgrid is nonlinear with numerous discrete variables and additional constraints. Traditional optimization methods are not the best solution due to tendency of getting stuck to a suboptimal solution. In this work, intelligent methods such as genetic algorithm (GA) and particle swarm optimization (PSO) have been applied for microgrid reconfiguration with shipboard power system (SPS) as an example. Proposed methods are capable to satisfy the operational constraints and consider load priorities. Graph theory is utilized to represent the microgrid network topology. Proposed intelligent reconfiguration algorithms were implemented using MATLAB and tested on 8-BUS and 13-BUS SPS models including distributed generations (DGs) and islands. Test systems were reconfigured in three different possible scenarios by considering load priority, load magnitude, and by combining these two simultaneously. Developed reconfiguration algorithm was also implemented in real time using controller-in-the-loop with real time digital simulator. Simulation results show satisfactory performance for several test case operating scenarios.