With a decade of rapid development of various renewable energies (e.g. wind and solar energies) and advanced energy storage technologies, the current energy structure and power generation mode have achieved dramatic transformation. Meanwhile, the rapid advancement of computer science and artificial intelligence has successfully obtained significant development and widespread applications in various energy systems to solve complex non-linear problems.

With large-scale renewable energy integration into modern power grids, it is crucial to reduce strong randomness and uncertainty to guarantee their economic and efficient integration and operation. 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 hard to model and analyse, thus advanced techniques are needed.

This Special Issue focuses on the most recent investigations and studies on advanced optimization and control strategies for power grids integrated with renewable energy. The targeted readers include both academic researchers and industry professionals. This Special Issue aims to provide a platform to promote up-to-date research and share promising ideas in the related fields. Both original research papers and review articles are welcomed.

Potential topics include but are not limited to the following:

• Power generators including photovoltaic units, fuel cells units, synchronous generators, permanent magnet synchronous generators, doubly-fed induction 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 including DC-DC converters, DC-AC inverters, AC-DC converters, DC-AC inverters, and VSC-HVDC transmission systems
• Power storage systems including batteries, supercapacitor energy storage systems, and superconducting magnetic energy storage systems
• Optimization techniques such as meta-heuristic algorithms, reinforcement learning, and neural networks
• Control strategies such as fuzzy logic control, sliding-mode control, perturbation/disturbance observer-based control, H-infinity control, backstepping control, and other feedback control techniques