Adaptive Inertia and Damping Tuning for VSG Using Improved Harris Hawks Optimization

Conventional virtual synchronous generator (VSG) control with fixed parameters cannot simultaneously achieve fast transient response and effective overshoot suppression, while adaptive VSG performance depends strongly on empirically tuned gains. This paper proposes an adaptive VSG control method based on an improved Harris Hawks optimization (IHHO) algorithm. Bounded nonlinear adaptation laws based on arctangent and hyperbolic tangent functions are developed to achieve smooth adjustment of virtual inertia and damping within prescribed limits. A dimensionless multi-index objective function is constructed by combining a normalized time-weighted active-power tracking index with an overshoot index, thereby balancing tracking accuracy, transient convergence, and overshoot suppression. To improve the optimization process, the Golden Sine strategy is introduced into the exploration stage to enhance search directionality, while Cauchy mutation is employed to maintain population diversity and improve the ability to escape local optima. Under consecutive active-power steps from 0 to 10 kW and from 10 to 20 kW, the proposed IHHO achieves overshoots of 5.7% and 7.2%, with settling times of 0.27 s and 0.24 s, respectively. Compared with the unoptimized adaptive VSG, the overshoot is reduced by 9.4 and 9.7 percentage points, while the settling time is shortened by 0.14 s and 0.13 s, respectively. Furthermore, the frequency-response analysis shows approximately 50% reductions in the magnitudes of the negative frequency-deviation peaks and approximately 41% reductions in the negative ROCOF peaks under the investigated conditions. Comparisons with the Grey Wolf Optimizer and conventional Harris Hawks optimization further demonstrate the effectiveness of the proposed IHHO-based adaptive gain-tuning method.