Hybrid Microgrid based on PID Controller with the Modified Particle Swarm Optimization

Microgrids (MG) are distribution networks encompassing distributed energy sources. As it obtains the power from these resources, few problems such as instability along with Steady-State (SS) issues are noticed. To address the stability issues, that arise due to disturbances of low magnitude. Small-Signals Stability (SSS) becomes mandatory in the network. Convergence at local optimum is one of the major issues noticed with the existing optimization algorithms. This paper proposes a detailed model of SSS in Direct Current (DC)-Alternate Current (AC) Hybrid MG (HMG) using Proportional Integral and Derivative Controller (PIDC) tuned with Modified Particle Swarm Optimization (MPSO) algorithm to alleviate such issues. The power is extracted from Renewable Energy Resources (RER), such as Photovoltaic (PV), Micro-Hydro (MH), and Wind Energy Conversation System (WECS). For tracking the power more efficiently, Maximum Power Point Tracking (MPPT) techniques are employed. Boost Converters (BC) are used and inverters are employed to convert DC to the AC. Here, the power flow is managed by the PIDC. If the Firing Angle (FA) is not properly determined, it results in instability and steady-state stability issues. To address this, the optimum tuning parameters are chosen for PIDC, by utilizing the MPSO. Finally, through experimentation analysis, the proposed system's performance is analyzed and compared with the existing algorithms and validated.