Modelling and Management of Grid with Grid-Forming Battery Energy storage

The rapid adoption of inverter-based resources (IBRs), such as grid-forming battery energy storage systems (BESS) and inverter-based loads (IBLs), is fundamentally transforming the dynamics of modern electrical grids. Unlike synchronous generators, these devices do not inherently contribute inertia, potentially impacting system stability, voltage regulation, and power quality. At the same time, grid-forming inverters (GFIs) in BESS have emerged as a promising solution to provide synthetic inertia and autonomous voltage and frequency support, especially in weak or islanded grids. However, the dynamic interaction between GFI-BESS and IBLs is complex, nonlinear, and not fully understood, necessitating advanced modeling and control strategies for optimal energy management and grid resilience.;;Despite the growing deployment of grid-forming battery energy storage systems (GFI-BESS) and inverter-based loads (IBLs), significant research gaps remain. Current dynamic models of GFI-BESS are either overly simplified or too complex for practical control and energy management applications. The interaction between GFI-BESS and IBLs is not well understood, particularly under varying grid strengths, with most studies assuming passive or static load models. Additionally, existing inverter-based load models often neglect the internal control dynamics that can critically affect grid stability. There is a lack of coordinated, real-time energy management frameworks that integrate grid-supportive functions like frequency regulation, virtual inertia, and voltage control, while considering battery constraints and load flexibility. Furthermore, most proposed control strategies are not validated under realistic scenarios with high IBL penetration or implemented on hardware platforms, limiting their practical relevance. Cyber-physical resilience and compliance with emerging grid codes are also largely overlooked. These gaps highlight the need for comprehensive modeling, adaptive control, and experimentally validated energy management strategies for future inverter-dominated power systems.;;The primary aim of this research is to develop comprehensive dynamic models and advanced energy management strategies for power grids with high penetration of grid-forming battery energy storage systems (GFI-BESS) and inverter-based loads (IBLs), in order to enhance grid stability, reliability, and operational efficiency under varying network conditions. The main objectives of this research project are to:;• develop accurate, control-oriented dynamic models of grid-forming BESS, capturing both inverter control behavior and battery characteristics. Model and analyze the dynamic behavior of major inverter-based loads (e.g., electric vehicle chargers, industrial drives) and their interactions with GFI-BESS under different grid strengths.;• investigate stability, power quality, and dynamic performance of distribution networks with high GFI-BESS and IBL penetration through time-domain and frequency-domain analysis.;• design adaptive control strategies and energy management systems that coordinate GFI-BESS operation for voltage and frequency regulation, synthetic inertia support, and optimal battery usage.;• develop and implement real-time coordination frameworks between GFI-BESS and IBLs for resilient and flexible grid support, including load-following and fault response capabilities.