Energy Management in a Dynamic Microgrid Using Genetic Algorithms

This paper presents an energy management strategy by opening and closing switches in a dynamic microgrid. This microgrid consists of several groups containing grid following (GFL) photovoltaic (PV) inverters, grid forming (GFM) energy storage and load which can be connected and disconnected from the main microgrid. Optimization for energy management seeks to minimize the energy consumed by the grid with the constraint of continuously supplying energy to a critical load. The algorithm is tasked with energy management is the genetic algorithm. The algorithm evaluates all the parameters of the microgrid and as a result, delivers the states of the switches of all the groups and the power reference for the energy storage. Finally, to observe the dynamic behavior of the microgrid states caused by the opening and closing of switches, the microgrid was modeled in the direct-quadrature frame. For this, the average models of the inverters with voltage control for the GFM group and with current control for the GFL groups were used.