Rapid advancement of various renewable energies including wind and solar energies, as well as advanced energy storage technologies dramatically change the current energy structure. Particularly, a power system is a large non-linear and dynamic power grid, thus it is critical to solve strong inherent randomness and uncertainty in current power grids with large-scale renewable energy integration, to guarantee their economic and stable operation. Meanwhile, the development of advanced technologies and novel methods using state-of-the-art computer science and artificial intelligence to deal with problems in the smart grid is essential, which has successfully achieved significant development and widespread applications in various energy systems to solve complex non-linear problems.
Hence, the exploitation and implementation of various advanced optimization and control techniques to deal with such problems are critical for efficiency and stability enhancement, including frequency regulation, voltage support, converter control, parameter/state identification and estimation, MPPT design, planning and dispatching, power and load forecast, etc. Such optimization/control problems are generally complex and difficult to model and analyse, such that advanced techniques are required.
This Research Topic aims to collate original papers about advanced optimization and control strategies applied to power grids integrated with renewable energy. The targeted readers include both academic researchers and industry professionals. This Research Topic aims to provide a platform to promote up-to-date research and share promising ideas in the related fields. Review articles describing the state of the art are also welcomed.
Potential topics include but are not limited to the following:
· Power generators: photovoltaic units, fuel cells units, doubly-fed induction generators, permanent magnet synchronous generators, doubly-fed reluctance generators, hybrid-excited synchronous generators, wind-turbine electric power units, multi-phase generators, thermoelectric generation systems, distributed electric power transmission, and distribution systems.
· Power electronics: DC-DC converters, AC-DC converters, DC-AC inverters, and VSC-HVDC transmission systems.
· Power storage systems: batteries, supercapacitor energy storage systems, and superconducting magnetic energy storage systems.
· Optimization methods including meta-heuristic algorithms, reinforcement learning & transfer learning, and neural networks.
· Control strategies including fuzzy logic control, sliding-mode control, perturbation/disturbance observer-based control, H-infinity control, backstepping control, and other feedback control strategies.
Rapid advancement of various renewable energies including wind and solar energies, as well as advanced energy storage technologies dramatically change the current energy structure. Particularly, a power system is a large non-linear and dynamic power grid, thus it is critical to solve strong inherent randomness and uncertainty in current power grids with large-scale renewable energy integration, to guarantee their economic and stable operation. Meanwhile, the development of advanced technologies and novel methods using state-of-the-art computer science and artificial intelligence to deal with problems in the smart grid is essential, which has successfully achieved significant development and widespread applications in various energy systems to solve complex non-linear problems.
Hence, the exploitation and implementation of various advanced optimization and control techniques to deal with such problems are critical for efficiency and stability enhancement, including frequency regulation, voltage support, converter control, parameter/state identification and estimation, MPPT design, planning and dispatching, power and load forecast, etc. Such optimization/control problems are generally complex and difficult to model and analyse, such that advanced techniques are required.
This Research Topic aims to collate original papers about advanced optimization and control strategies applied to power grids integrated with renewable energy. The targeted readers include both academic researchers and industry professionals. This Research Topic aims to provide a platform to promote up-to-date research and share promising ideas in the related fields. Review articles describing the state of the art are also welcomed.
Potential topics include but are not limited to the following:
· Power generators: photovoltaic units, fuel cells units, doubly-fed induction generators, permanent magnet synchronous generators, doubly-fed reluctance generators, hybrid-excited synchronous generators, wind-turbine electric power units, multi-phase generators, thermoelectric generation systems, distributed electric power transmission, and distribution systems.
· Power electronics: DC-DC converters, AC-DC converters, DC-AC inverters, and VSC-HVDC transmission systems.
· Power storage systems: batteries, supercapacitor energy storage systems, and superconducting magnetic energy storage systems.
· Optimization methods including meta-heuristic algorithms, reinforcement learning & transfer learning, and neural networks.
· Control strategies including fuzzy logic control, sliding-mode control, perturbation/disturbance observer-based control, H-infinity control, backstepping control, and other feedback control strategies.