基于联合时序场景和源网荷协同的分布式光伏与储能优化配置

Optimal Configuration of Distributed Photovoltaic and Energy Storage System Based on Joint Sequential Scenario and Source-Network-Load Coordination

主动配电网可通过协同调度灵活性资源促进分布式光伏(DPV)电量消纳,为此提出基于联合时序场景和源-网-荷协同的DPV与储能系统(ESS)联合优化配置方法。基于动态弯曲时间特性提出光-荷联合时序场景生成方法,处理源-荷不确定性和时序相关性;建立源、网、荷、储灵活性资源数学模型;以DPV全年总发电量最大为目标,兼顾配电网经济性,建立DPV与ESS联合优化配置的混合整数线性规划模型。以某51节点标准测试系统为例验证所提方法的有效性,量化分析不同灵活性资源对DPV消纳的提升效果。

Active distribution network can promote distributed photovoltaic(DPV) energy consumption through optimal scheduling of flexible resources. Therefore, this paper proposes a joint optimal configuration method of DPV and energy storage(ESS) based on joint sequential scenario and source-network-load coordination. An DPV-load joint temporal scene generation method is proposed to handle the source-load uncertainty and temporal correlation based on the characteristics of dynamic time warping. And it establishes the mathematical model of source-network-load-ESS resources. Then, it presents the mixed integer linear programming model of DPV and ESS joint optimal configuration, and the goal is to maximize the annual total power generation of DPV with the consideration of the distribution network economy. And it takes the 51-node standard test system as an example to analyze the correctness and effectiveness of the proposed method. And the effect on DPV consumption improvement of different flexible resources is quantitatively analyzed.