The increasing demand for carbon neutralization requires more renewable energy in power systems. Thanks to the advance of power electronics technology, power converters with increased power levels and density enable more distributed energies to be delivered into the power grid. However, compared with the traditional power grid, the power electronics systems which have higher dynamic response speed but less inertia introduce challenges into the robustness of modern power grid. Also, high uncertainty and intermittency of renewable energy sources such as solar and wind power also increase the power dispatching complexity. Developments of statistical learning and stochastic optimal control bring new possibility to address the above problems.
Aiming at addressing the aforementioned problems, in the past decades, much effort has been dedicated into investigating solutions to enhance the stability of modern power systems with increasing penetration of power electronics equipment including energy storage, improved control strategies, artificial intelligence assisted power dispatching technology and decentralized energy management. This topic will present and encourage the dissemination of emerging research works in the following aspects:
- Statistical learning-based modelling and simulation for power system with new energy access;
- Robust network control for the modern power grid with power electronics devices;
- Power quality evaluation of large-scale new energy generation systems;
- Energy management of power grid with high proportion of uncertain renewable energy sources.
Prospective authors are welcome to submit original contributions which utilize novel approaches to address the practical problems in the industry. Topics of interest include, but are not limited to:
- Modelling of power converters
- Energy storage system operation and design
- Distributed generation prediction
- Reliability, diagnosis and protection of multi-converters systems
- Renewable energy generation
- Photovoltaic energy generation low-voltage ride-through methodologies
- Micro-grid operation and energy management
- Residential renewable energy harvesting
- Artificial intelligence assisted economic power dispatching
- Application of machine learning technology in power system operations and planning
- Electricity market policy and optimization
The increasing demand for carbon neutralization requires more renewable energy in power systems. Thanks to the advance of power electronics technology, power converters with increased power levels and density enable more distributed energies to be delivered into the power grid. However, compared with the traditional power grid, the power electronics systems which have higher dynamic response speed but less inertia introduce challenges into the robustness of modern power grid. Also, high uncertainty and intermittency of renewable energy sources such as solar and wind power also increase the power dispatching complexity. Developments of statistical learning and stochastic optimal control bring new possibility to address the above problems.
Aiming at addressing the aforementioned problems, in the past decades, much effort has been dedicated into investigating solutions to enhance the stability of modern power systems with increasing penetration of power electronics equipment including energy storage, improved control strategies, artificial intelligence assisted power dispatching technology and decentralized energy management. This topic will present and encourage the dissemination of emerging research works in the following aspects:
- Statistical learning-based modelling and simulation for power system with new energy access;
- Robust network control for the modern power grid with power electronics devices;
- Power quality evaluation of large-scale new energy generation systems;
- Energy management of power grid with high proportion of uncertain renewable energy sources.
Prospective authors are welcome to submit original contributions which utilize novel approaches to address the practical problems in the industry. Topics of interest include, but are not limited to:
- Modelling of power converters
- Energy storage system operation and design
- Distributed generation prediction
- Reliability, diagnosis and protection of multi-converters systems
- Renewable energy generation
- Photovoltaic energy generation low-voltage ride-through methodologies
- Micro-grid operation and energy management
- Residential renewable energy harvesting
- Artificial intelligence assisted economic power dispatching
- Application of machine learning technology in power system operations and planning
- Electricity market policy and optimization
