基于动态集群划分的微电网风光储协同优化运行策略OA

Under the carbon peaking and carbon neutrality goals,the high integration of new energy sources like photovoltaics(PV)into the power system makes it difficult for traditional dispatching schemes to effectively handle their randomness and volatility in output.PV curtailment occurs frequently and local counter-peak regulation further exacerbates the peak-valley load difference.To address these issues,focused on a microgrid with large-scale PV integration,and a coordinated optimization strategy for wind,PV,and storage operations,considering dynamic clustering and partitioning of PV clusters was proposed.First,with the goal of improving the smoothness of PV output,a dynamic clustering division based on trend inconsistency distance was performed using the K-means algorithm.The optimal clustering scheme and dynamic adjustment strategy were determined using sum of squared error(SSE)indicator.Next,based on the clustering results,a coordinated optimization strategy for wind,PV,and storage in the microgrid was proposed,integrating the operational costs of generation,load,and storage.Finally,case study analysis demonstrated that the proposed method effectively utilized the smoothing effect of PV clusters,enhanced the integration level of new energy,and achieved multiple operational objectives such as improving system economic efficiency and peak shaving and valley filling.