To build a sustainable and low-carbon power system, renewable energy sources (RESs), e.g., wind and solar, have been rapidly developed and achieved a considerable share in power systems. Concurrently, various new types of loads, such as electric vehicles and distributed energy resources, are also increasing on the demand side. The significant changes in the source and load sides can enhance the energy structure and reduce carbon dioxide emissions. Uncertainties related to wind power, solar power, electric vehicles, and distributed energy resources will present significant challenges to the secure and economical operation of power systems.
How to effectively manage a power system amid various uncertainties is a challenging and crucial issue that has received significant attention from both academia and industry. It requires extensive research on uncertainty modeling, risk perception, decision-making under uncertainty, operational modeling, and strategies using multidisciplinary approaches in engineering, operations research, and economics. We are seeking innovative ideas and insights for addressing the challenges of power systems operations under multiple uncertainties through this Research Topic.
The themes of this Research Topic include but are not limited to:
1. Modeling and forecasting techniques for renewable energy resources,
2. Modeling and forecasting techniques for demand-side management,
3. Risk Assessment for power systems under multiple uncertainties,
4. Power system risk modeling and prevention for extreme meteorological disasters,
5. Optimal dispatch for power systems under multiple uncertainties,
6. Modeling of carbon emission flow and carbon-power coordinated operation under uncertainty,
7. Advanced methods of decision-making under uncertainty with applications to power systems operations,
8. Data analytics and machine learning for power systems under multiple uncertainties.
Keywords:
power systems, renewable energy resources, uncertainty modeling, risk management, optimal dispatch
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.
To build a sustainable and low-carbon power system, renewable energy sources (RESs), e.g., wind and solar, have been rapidly developed and achieved a considerable share in power systems. Concurrently, various new types of loads, such as electric vehicles and distributed energy resources, are also increasing on the demand side. The significant changes in the source and load sides can enhance the energy structure and reduce carbon dioxide emissions. Uncertainties related to wind power, solar power, electric vehicles, and distributed energy resources will present significant challenges to the secure and economical operation of power systems.
How to effectively manage a power system amid various uncertainties is a challenging and crucial issue that has received significant attention from both academia and industry. It requires extensive research on uncertainty modeling, risk perception, decision-making under uncertainty, operational modeling, and strategies using multidisciplinary approaches in engineering, operations research, and economics. We are seeking innovative ideas and insights for addressing the challenges of power systems operations under multiple uncertainties through this Research Topic.
The themes of this Research Topic include but are not limited to:
1. Modeling and forecasting techniques for renewable energy resources,
2. Modeling and forecasting techniques for demand-side management,
3. Risk Assessment for power systems under multiple uncertainties,
4. Power system risk modeling and prevention for extreme meteorological disasters,
5. Optimal dispatch for power systems under multiple uncertainties,
6. Modeling of carbon emission flow and carbon-power coordinated operation under uncertainty,
7. Advanced methods of decision-making under uncertainty with applications to power systems operations,
8. Data analytics and machine learning for power systems under multiple uncertainties.
Keywords:
power systems, renewable energy resources, uncertainty modeling, risk management, optimal dispatch
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.