A New Scheme of Harris Hawk Optimizer With Memory Saving Strategy (HHO-MSS) for Controlling Parameters of Power System Stabilizer and Virtual Inertia in Renewable Microgrid Power System

Renewable microgrid power systems confront a typical stability challenge due to the deficiency of damping and inertia properties. This stability can be maintained by controlling the parameters of the Power System Stabilizer (PSS) and Virtual Inertia (VI). This paper proposes a new approach for controlling the optimal parameters of PSS and VI in the renewable microgrid power system consisting of a conventional generator, Photovoltaic Energy System (PVES), Wind Turbine Energy System (WTES), and Battery Energy Storage System (BESS). A new scheme of Harris Hawk Optimizer with Memory Saving Strategy (HHO-MSS) is proposed as the robust optimizer. Benson Scalarization Technique is also introduced to combine objective functions dependent on the damping factor and damping ratio. Using the Friedman Ranking Test, superior performances in exploration and exploitation processes conducted by HHO-MSS over the other modified versions of HHO and basic algorithms. Moreover, significant improvements have been conducted by HHO-MSS, especially in the convergence curve characteristics and the proportion between exploration and exploitation processes. The fitness values that have been produced by HHO-MSS are 9% to 26% better than the other algorithms. The optimal parameters are investigated by eigenvalue and time domain analysis in low, mid, high, and full RES penetrations. In the low and mid RES penetration analysis, PSS has better stability improvements than VI. On the other hand, VI has better stability improvement than PSS in high and full RES penetration analysis. Besides that, the best stability improvements in all RES penetrations with optimal Rate of Change of Frequency (RoCoF) reduction, smallest overshoot, and smoothest frequency and power angle responses are established by the proposed approach that controlling the optimal parameters of PSS and VI by using HHO-MSS. Moreover, the performance indexes validation has justified the proposed approach has the highest average error reduction of 47.26% over the existing approaches.