About this Research Topic
Modeling techniques include physics-based or first principle modeling, system identification, machine learning techniques, and deep learning techniques. Parameter identification and verification is crucial for trustable models. Control systems include, but are not limited to, advanced PID controllers, classical or adaptive model predictive control (MPC) and intelligent controllers.
The goal of this Research Topic is to develop models and control methods that enhance the recent responses of energy sources to be significantly faster and more capable than existing options. Thermal plants include subcritical and supercritical generation units fed by gas, oil, or coal. The practical goal is to strengthen the recent networks to be more secure and stable with less pollution and a lower environmental impact. As such, renewables including wind, solar, hydraulic, and geothermal sources have more specific, but generally similar, control goals. However, aside from this general aim, some specific desired outcomes of this Research Topic are as follows:
- Improving online monitoring of safety and energy efficiency
- Improving fault detection and diagnosis
- Training technicians and future engineers
- Upgrading the automation of existing power units
- Enhancing ancillary services
- Helping create an overall robust generation system that increases the feasibility of growing the share of renewables in the energy mix
The scope of this Research Topic includes the control and automation of energy resources. Essential elements include improved accuracy of modeling and improved control performance over existing or previous strategies. Modeling and control via machine learning techniques, advanced linear and nonlinear control techniques, and model predictive control are preferable. However, authors are welcome to submit different strategies of control subject to their practical feasibility.
Therefore, the essential scope of this Research Topic can be stated as the following points:
- Modeling by first principles with parameter identification via robust optimization techniques
- Modeling by machine learning and deep learning techniques
- System identification and state estimation (online and offline)
However, if models are available in advance, then the focus on control systems will include:
- Robust and adaptive control techniques
- Model predictive control (classical, adaptive, explicit, and so on)
- Intelligent control systems
Keywords: Control, Automation, Thermal Power Plants, Energy efficiency, Decarbonization
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.