Table 2 Comparison of different indicators of control strategies.

From: The potential of combined robust model predictive control and deep learning in enhancing control performance and adaptability in energy systems

Parameter/Scenario

Baseline

RMPC

RMPC with Deep Learning

Control Strategy

Simple feedback control

Robust Model Predictive Control

RMPC with Deep Learning adjustment

CHP Power Output Stability

Moderate fluctuations

Reduced fluctuations

Minimally fluctuating, highly stable

Hydrogen Production

Baseline production levels

Improved production levels

Optimized production levels with better adaptation

Methane Production

Baseline production levels

Improved production levels

Optimized production levels with better adaptation

Adaptability to System Changes

Low adaptability

Improved adaptability due to predictive control

High adaptability with real-time adjustments

Control Accuracy

Baseline accuracy

Improved accuracy

Highest accuracy

Energy Consumption

Baseline energy usage

Reduced energy usage

Significantly reduced energy usage

Robustness to Disturbances

Low robustness

Improved robustness

Highest robustness to dynamic operating conditions

Implementation Complexity

Low complexity

Moderate complexity

High complexity due to deep learning integration

Simulation Complexity

Simple simulation

More complex simulation with predictive modeling

Most complex simulation with predictive and adaptive modeling

Overall Performance Improvement

Baseline performance

Improved performance

Significant performance enhancement