Fuzzy-neural controller design for stability enhancement of microgrids

In this paper a new architecture of MicroGrid (MG) is presented. Intelligent control strategies are applied for stability enhancement in different modes. This new structure of MG includes four types of microsources (MS) connected to low voltage (LV) side of distribution system (DS) and a synchronous generator Distributed generation. Due to the nonlinear and stochastic behavior of the system, a fuzzy-neural-network control strategy is applied. By this method, there is no need of storage device and controllable loads which are not economical in distribution networks. LV- side of MG with synchronous DG meets loads and generation rapidly. The proposed MG architecture is more practical due to the presence of various DGs in distribution network. Regarding the elimination of some equipment like storage device and controllable loads, this model of MG is more economical and practical. As a result, stability in different modes (parallel, transient, and autonomous modes) is improved. Results show that the proposed architecture with the intelligent controller solve stability problem of MicroGrids with good consideration to other issues related to MicroGrid such as economics, protection, reliability, and so on. The most important point is that in this architecture, the synchronous DG is not added to stabilize MicroGrid, but this architecture is proposed because of its practical issues. The most important benefit of this research is that any DG unit which can provide power with the frequency of 50 Hz would be able to connect directly to DS.