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Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
Published on: February 14, 2025
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Decentralized Event-Triggered Adaptive Dynamic Programming Approach for Electric-Gas Coupling Energy Systems With
IEEE Transactions on Cybernetics
|September 8, 2025
Summary
A new adaptive control scheme optimizes integrated electric-gas systems using decentralized event-triggered control and adaptive dynamic programming. This method reduces computational load and communication waste while ensuring system stability.
Area of Science:
- Control Systems Engineering
- Energy Systems Analysis
- Artificial Intelligence in Engineering
Background:
- Integrated electric-gas systems present complex control challenges due to partially unknown dynamics and interdependencies.
- Traditional control methods often struggle with the high dimensionality and nonlinearities inherent in these coupled systems.
- Efficient resource utilization and computational complexity are critical concerns in real-time system management.
Purpose of the Study:
- To develop a novel online adaptive control scheme for optimal control of integrated electric-gas systems.
- To address challenges posed by partially unknown system dynamics and reduce communication overhead.
- To ensure system stability and prevent Zeno behavior in the control strategy.
Main Methods:
- Modeling the electric-gas coupling network in state-space form.
- Employing neural networks (NNs) for online approximation of unknown dynamics (identifier NN) and optimal value functions (critic NN).
- Designing decentralized event-triggered control strategies with a dead-zone mechanism to minimize updates.
Main Results:
- The proposed scheme effectively approximates unknown system dynamics and optimal value functions online.
- The decentralized event-triggered control with dead-zone significantly reduces computational complexity and communication resource usage.
- Lyapunov theory confirms the uniform ultimate boundedness stability of the closed-loop system and the exclusion of Zeno behavior.
Conclusions:
- The developed online adaptive control scheme offers an effective solution for optimal control of integrated electric-gas systems.
- The integration of decentralized event-triggered mechanisms and adaptive dynamic programming provides a robust and efficient control strategy.
- The proposed method demonstrates practical applicability and effectiveness through numerical simulations.
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