基于数据驱动的主动配电网分布鲁棒有功无功协调优化

Data-driven Distributionally Robust Coordinated Optimization of Active and Reactive Power in Active Distribution Networks

为充分发挥分布式电源与可控设备有功无功出力在配电网优化中的作用,减少分布式电源随机出力与负荷波动对系统的影响,首先,从有功无功协调优化角度出发,以有载调压变压器、光伏机组、储能系统、微型燃气轮机及无功补偿设备为控制手段,建立以网损最小为优化目标的主动配电网有功无功协调优化模型;然后,在协调优化模型的基础上,采用场景分析法处理光伏出力及负荷预测的不确定性,并以l-2范数约束构建场景概率分布的不确定集,建立了基于数据驱动的主动配电网分布鲁棒有功无功协调优化模型,采用列与约束生成算法进行求解.经IEEE33节点系统验证,结果证明了协调优化策略能有效地降低网损与分布鲁棒优化策略能有效应对系统中的不确定性.

In order to take full advantage of the active and reactive power output of distributed generation and controllable equipment in distribution network optimization,and reduce the influence of random output and load fluctuation of distributed generation on the system,an active and reactive power coordination optimization model of active distribution network is established from the point of view of active and reactive power coordination optimization,with on-load tap changers,photovoltaic unit,energy storage system,micro gas turbine and reactive power compensation equipment as control means,aiming at minimizing network loss.Then,on the basis of the coordination optimization model,the uncertainty of PV output and load forecasting is dealt with by scenario analysis method,and the uncertainty set of scenario probability distribution is constructed with I-2 norm constraint.A data-driven distributed robust active and reactive coordination optimization model of active distribution network is established,which is solved by column and constraint generation algorithm.Verified by IEEE33-bus system,the results show that the coordinated optimization strategy can be effectively reduce the network loss and the distributionally robust optimization strategy can be effectively dealt with the uncertainty in the system.