基于风光数据驱动不确定集合的配电网与多微网鲁棒经济调度

随着风电和光伏等可再生能源通过多微网(multiple microgrids,MMGs)的形式接入配电网(distribution network,DN),其不确定性会给配电网与多微网系统联合运行的可靠性、经济性带来挑战。对此,文章提出了一种考虑风光相关性的配电网与多微网数据驱动鲁棒调度方法。首先采用分布式调度方法建立配电网与多微网调度框架,分别建立配电网调度模型与微网二阶段鲁棒调度模型,以联络线功率作为两者的耦合参数;考虑风光出力的不确定性与时空相关性,采用数据驱动算法构建风-光出力不确定集合,从而建立微网数据驱动鲁棒调度模型;最后提出一种基于极限场景的改进列约束生成算法(column-and-constraint generation,C&CG)求解微网鲁棒调度问题,并采用目标级联分析法(analytical target cascading,ATC)对配电网与多微网整体调度问题进行求解。仿真结果表明,该配电网与多微网的数据驱动鲁棒调度策略可以捕捉风-光时空相关性,在保证系统调度鲁棒性时提高调度的经济性,并具有良好的收敛性。

Data-Driven Robust Economic Dispatch for Distribution Network and Multiple Micro-grids Considering Correlativity of Wind and Solar Output

As renewable energy generations represented by wind and photovoltaic power connect to the distribution network (DN) through multiple micro-grids (MMGs), the uncertainty will bring challenges to the reliability and economy of the operation of the DN and MMGs. In response to this, this paper proposes a data-driven robust dispatch method for DN and MMGs considering correlation between wind and solar output. Firstly, a distributed dispatch method is adopted to establish the dispatch model of the DN and a two-stage dispatch model of the MMGs, with the tie-line power as the coupling parameter of the two. Aiming at the uncertainty of renewable energy output as well as the temporal and spatial correlations, the wind-solar output ellipsoid uncertain set is constructed based on the data-driven algorithm, thereby establishing the two-stage data-driven robust dispatch model of the micro-grid. Finally, an improved column and constraint generation algorithm based on extreme scenarios is proposed to solve the robust dispatch problem of the micro-grid, and the analytical target cascading method is used to solve the overall dispatch problem of DN and MMGs. The simulation results show that the proposed method can capture the spatial-temporal correlation between wind and solar, improve the economy of dispatch while ensuring the robustness of the DN and MMGs dispatch, and has good convergence.