Aggregating Inverter-Based Resources for Fast Frequency Response: A Nash Bargaining Game-Based Approach

Abstract

This paper proposes a multi-objective optimization (MOO) approach for grid-level frequency regulation by aggregating inverter-based resources (IBRs). Virtual power plants (VPPs), acting as aggregators, can efficiently respond to dynamic response requirements from the grid. Through parametric modeling, grid-level frequency regulation requirements are accurately quantified and translated into a feasible parameter region defined by device-level parameters. Based on this feasible region, an MOO model is developed to address the conflicting demands of IBRs during frequency response. A Nash bargaining game-based approach is then employed to optimally allocate regulation requirements within the VPP, balancing the various demands of the IBRs. Numerical experiments demonstrate the effectiveness of the proposed method in enhancing frequency stability and improving coordination among IBRs.