基于自注意力扩散强化学习的配电网光伏承载力提升方法OA

To address the issue of insufficient accommodation capacity of distribution networks caused by high penetration of distributed photovoltaic(PV)integration,an enhancement method for PV accommodation capacity of distribution networks based on self-attention diffusion reinforcement learning is proposed.Aiming to enhance the PV accommodation capacity of the distribution network,a multi-objective optimization mathematical model is established from the perspective of collaborative optimization of distributed PV inverters on the source side,static var compensators on the grid side,flexible loads,and battery energy storage controllers.The proposed model takes into account both voltage deviation and system network loss indicators,with the goals of maximizing the distributed PV allowable capacity and minimizing the total operation cost.While satisfying the operation constraints,the method uses a diffusion mechanism to rapidly adapt to complex and uncertain environments,and leverages a self-attention mechanism to enable parallel reading of batch data,thereby improving training speed and solution efficiency.Finally,simulation analysis of a case study verifies the effectiveness and economic feasibility of the proposed method.