Optimal Operation

Optimal operation research focuses on finding the best strategies for managing complex systems to maximize efficiency, minimize costs, and achieve specific goals, such as carbon neutrality or resource optimization. Current research heavily utilizes deep reinforcement learning (DRL), employing architectures like Deep Deterministic Policy Gradients (DDPG) and Soft Actor-Critic (SAC), often enhanced by techniques like graph convolutional networks to leverage system structure and improve performance. These advancements are impacting diverse fields, from energy management (power grids, reservoirs) and transportation (vehicle-to-grid) to industrial processes, enabling more sustainable and economically viable operations through data-driven decision-making.