Optimization of energy storage capacity using distributionally robust optimization for converter-based grids

Abstract

As the penetration of converters into the grid continues to increase, converter-based power sources are replacing synchronous machine-based power sources, leading to the establishment of a converter-based grid (CBG) for regulating grid frequency and voltage. At this stage, energy storage becomes a necessity to support the operation of the CBG. The grid-interfacing inverters are transitioning from the conventional grid-following (GFL) control to the grid-forming (GFM) control. within the context of this research paper, considering the premise that energy storage capacity must meet CBG stability constraints and accommodate the integration of renewable energy sources, a capacity optimization model is constructed based on distributional robust optimization. The primary objective of this model is to minimize the overall cost with the allocation of energy storage capacity as the central focus. The study includes case analyses conducted within an IEEE-14 node CBG. The results of the case analyses confirm that the determined energy storage capacity can ensure the stable operation of the CBG and meet the demands for integrating renewable energy sources.