Gene

Inertia

Electrical engineering

Physics

Engineering

Control engineering

Artificial intelligence

Power (physics)

Chemistry

Renewable energy

Fuzzy control system

Automatic frequency control

Control (management)

Microgrid

Computer science

Control theory (sociology)

Biochemistry

Fuzzy logic

Quantum mechanics

Robustness (evolution)

Classical mechanics

Telecommunications

Electric power system

IEEE Access

Maintaining frequency stability of low inertia microgrids with high penetration of renewable energy sources (RESs) is a critical challenge. Solving this challenge, the inertia of microgrids would be enhanced by virtual inertia control-based energy storage systems. However, in such systems, the virtual inertia constant is fixed and selection of its value will significantly affect frequency stability of microgrids under different penetration levels of RESs. Higher frequency oscillations may occur due to the fixed virtual inertia constant or unsuitable selection of its value. To overcome such a problem and provide adaptive inertia control, this paper proposes a self-adaptive virtual inertia control system using fuzzy logic for ensuring stable frequency stabilization, which is required for successful microgrid operation in the presence of high RESs penetration. In this concept, the virtual inertia constant is automatically adjusted based on input signals of real power injection of RESs and system frequency deviations, avoiding unsuitable selection and delivering rapid inertia response. To verify the efficiency of the proposed control method, the contrastive simulation results are compared with the conventional method for serious load disturbances and various rates of RESs penetration. The proposed control method shows remarkable performance in transient response improvement and fast damping of oscillations, preserving robustness of operation.

Self-Adaptive Virtual Inertia Control-Based Fuzzy Logic to Improve Frequency Stability of Microgrid With High Renewable Penetration