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

Abstract

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. INDEX TERMS Frequency control, fuzzy logic, intelligent control, islanded microgrid, virtual inertia control, virtual synchronous generator

Microgrid Frequency Fluctuation Attenuation Using Improved Fuzzy Adaptive Damping-Based VSG Considering Dynamics and Allowable Deviation

“…According to (16), the response of ∆P with the virtual natural frequency decreasing from ξ 5 to ξ 1 is depicted in Figure 7. When the system is undamped, the time for the frequency deviation to reach its peak (t p ) and the corresponding output (∆f p ) can be obtained as (19) and 20, respectively: It can be seen that as ξ increases from 0 to 2, the overshoot becomes smaller and it turns to be 0 when ξ > 1 (overdamped). In terms of the peak time, it is related to not only ξ but also ω na .…”

“…Undoubtedly, these studies have laid the ground for enhancing the power quality and stability of the grid and the microgrids by the use of VSG technologies. However, the addition of the traditional VSG with the constant virtual inertia and damping values cannot completely avoid the risks of frequency and active power oscillation in view of the penetration levels of the external load disturbances [19], especially when the inertia and damping values stand at the low positions, but if the inertia and damping are large, the transient control performance would be sacrificed [20]. To tackle these problems, several up-to-date self-adaptive control methods have been developed in [21][22][23][24][25][26].…”

Grid Integration of Solar Photovoltaic System Using Machine Learning-Based Virtual Inertia Synthetization in Synchronverter

“…The gridtied RES connection via static DC-AC converters or inverters often has minimal inertial response for the stability of grid voltage and frequency due to the lack of rotating parts, unlike the synchronous machine (SM)-based conventional power generation [2]. As the penetration of distributed generation (DG) units becomes higher, the total inertia of the power system decreases over the years [3]. Hence, the frequency fluctuation of the grid cannot be damped by inertia effectively [4].…”

Combined Primary Frequency and Virtual Inertia Response Control Scheme of a Variable-Speed Dish-Stirling System

“…Hence, there have been various attempts to design virtual inertia response (VIR) algorithms by making use of the stored kinetic energy in the rotating mass of the WTG to emulate the conventional inertia so that the rate of change of frequency (ROCOF) can be effectively reduced in the first few seconds following the disturbance [23]. The VIR control schemes are designed for both interconnected ac/dc systems [24], multi-terminal dc system [25], and microgrid systems [26][27][28][29], utilizing different control schemes such as Hinfinity control [27], derivative control [28], fuzzy-logic control [29], among others. Unfortunately, these VIR controller designs are not applicable for the DS system because the prime mover (the turbine) of a wind generator operates on a completely different principle from that of the Stirling engine in a VSDS generating system.…”