Distributed component-level modeling and control of energy dynamics in electric power systems
For power system engineers, it addresses the challenge of controlling fast, heterogeneous, converter-dominated networks with a scalable distributed approach.
The paper extends an energy space modeling framework for converter-dominated power systems, proposing a distributed control architecture with provable convergence that uses only local states and neighbor information. Validation on voltage and frequency regulation shows improved transient/steady-state performance with reduced control effort.
The widespread deployment of power electronic technologies is transforming modern power systems into fast, nonlinear, and heterogeneous networks. Conventional modeling and control approaches, rooted in quasi-static analysis and centralized architectures, are inadequate for these converter-dominated systems operating on fast timescales with diverse and proprietary component models. This paper adopts and extends a previously introduced energy space modeling framework grounded in energy conservation principles to address these challenges. We generalize the notion of a port interaction variable, which encodes energy exchange between interconnected components in a unified manner. A multilayered distributed control architecture is proposed in which dynamics of each component are lifted to a linear energy space through well-defined mappings. Distributed control with provable convergence guarantees is derived in energy space using only local states and minimal neighbor information communicated through port interactions. The framework is validated using two examples: voltage regulation in an inverter-controlled RLC circuit and frequency regulation of a synchronous generator. The energy-based controllers show improved transient and steady-state performance with reduced control effort compared to conventional methods.