基于概率盒的考虑配电网源荷双侧不确定性多场景鲁棒优化调度方法

A Multi-scenario Robust Optimal Scheduling Method of Distribution Network Considering Source-side and Load-side Uncertainty Based on the Probability-box

针对负荷及可再生能源预测功率曲线不确定性对配电网调度计划的影响,提出了一种含多类型分布式能源的鲁棒优化调度模型。同时考虑源荷功率曲线预测误差及其概率分布参数的不确定性,基于概率盒理论生成模拟运行场景。为避免最劣场景的保守性,引入不确定性调节参数约束模拟场景与预测场景的偏离程度,进而构建恶劣场景集。以配电网综合经济成本最小为目标,分布式能源机组出力计划为决策变量,建立了基于不确定性场景的日前调度鲁棒优化模型。最后,在IEEE 33节点配电系统上进行仿真,分析结果表明该方法能够协调鲁棒性与经济性在决策优化中的矛盾,验证了模型的有效性。

Aiming at the influence of load and renewable energy predicted power curves uncertainty on distribution network scheduling,an optimal scheduling model with multiple types of distributed energy generation is constructed in this paper.The prediction error of the power curves and the uncertainty of its probability distribution parameters are considered,and the simulated operating scenarios are generated based on the probability-box theory.In order to avoid the conservativeness,the uncertainty adjustment parameters are introduced to constrain the deviation degree between the simulated scenario and the predicted scenario,and then the set of worst scenarios is constructed.A day-ahead robust optimization model based on the uncertain scenarios set is established with the goal of minimizing the comprehensive economic cost,and the output plan of distributed energy generation units is taken as the decision variable.Finally,the simulation is carried out on IEEE 33-bus system.The analysis results show that the proposed method can coordinate the contradiction between robustness and economy in decision optimization,which verify the effectiveness of the model.