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Distributed component-level modeling and control of energy dynamics in electric power systems

Hiya Gada, Rupamathi Jaddivada, Marija Ilic

Abstract

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.

Distributed component-level modeling and control of energy dynamics in electric power systems

Abstract

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.

Paper Structure

This paper contains 17 sections, 3 theorems, 53 equations, 7 figures.

Table of Contents

  1. Introduction
  2. Distributed control problem formulation
  3. Energy-based modeling of a component
  4. Preliminaries
  5. Energy space dynamic model
  6. Distributed control problem formulation in energy space
  7. Multilayered distributed control architecture
  8. Distributed control problem posing in energy space
  9. Energy-based component-level control
  10. Energy-based feedback linearization control
  11. Energy-based sliding mode control (SMC)
  12. Examples
  13. Voltage regulation in an RLC circuit
  14. Constant power load
  15. Time-varying power load
  16. ...and 2 more sections

Key Result

Theorem 4.1

Suppose that, for each component $\Sigma_i$: Then, solving Problem energy_control_objectives solves Problem prob:control_objectives.

Figures (7)

  • Figure 1: Interconnected system comprising two components $\Sigma_1$ and $\Sigma_2$ with local controllable inputs $u_1, u_2$, port inputs $r_1, r_2$, and exogenous disturbance $m_2$
  • Figure 2: Multilayered distributed control architecture for a component $\Sigma_i$
  • Figure 3: RLC circuit with an inverter-controlled voltage source $u^{vs}$ ($\Sigma_1$) supplying power to a black-box with unknown internal dynamics ($\Sigma_2$)
  • Figure 4: System response of the RLC circuit under proportional benchmark control \ref{['eqn:prop_control']}, energy-based FBLC, and energy-based SMC for a constant power load of $1~\text{kW}$, with the objective of stabilizing and regulating the terminal voltage $v_1$ to $80~\text{V}$
  • Figure 5: System response of the RLC circuit under nonlinear benchmark control \ref{['eqn:brayton_moser']}, energy-based FBLC, and energy-based SMC for a time-varying power load, with the objective of stabilizing and regulating the terminal voltage $v_1$ to $80~\text{V}$
  • ...and 2 more figures

Theorems & Definitions (15)

  • Definition 1: Stored energy
  • Definition 2: Stored energy in tangent space
  • Definition 3: Dissipation
  • Definition 4: Dissipation in tangent space
  • Definition 5: Time constants
  • Definition 6: Instantaneous power
  • Definition 7: Rate of change of generalized reactive power
  • Definition 8: Instantaneous power in tangent space
  • Definition 9: Interaction variables
  • Theorem 4.1: Inter-layer consistency for output tracking
  • ...and 5 more