Energy Dispatch

Energy dispatch optimizes the allocation of energy resources to meet demand, minimizing costs and emissions while ensuring grid stability. Current research heavily utilizes deep reinforcement learning (DRL) algorithms, such as DQN, DDPG, and PPO, to manage the complexities of integrating intermittent renewable sources and diverse loads, often within microgrid settings or for applications like charging electric vehicles. These advanced techniques address uncertainties inherent in renewable generation and fluctuating demand, leading to more efficient and robust energy systems. The resulting improvements in cost-effectiveness and grid reliability have significant implications for both decarbonization efforts and the broader energy sector.