计及新能源及负荷不确定性的多能微网系统两阶段随机规划方法

以电-热-气多能微网系统为研究对象,针对新能源与负荷的不确定性,提出基于分位数梯度提升决策树(quantile gradient boosting regression tree,QGBRT)的分位点-置信区间预测方法,并结合机会约束规划处理不确定性,在此基础上建立了基于能源集线器的日前两阶段随机规划调度优化模型,以置信区间形式,从统计层面反映机组可调控裕度,为日内和实时调度提供可信度参考。其中,QGBRT分位点-置信区间预测方法采用描述不确定性量的Pinball函数为损失函数,预测结果作为机会约束规划的约束信息输入。同时为了充分利用日前不断更新的信息,以及缓和日内调度计划制定的压力,日前第一阶段根据已发布信息,确定微网各设备的启停状态与交易能量状态量,日前第二阶段利用更新的信息,在第一阶段的基础上调整优化设备出力,实现日前的精准优化调度,以适用于实际调度。最后以一个典型的含多能微网系统的居民区为例,验证了所提考虑不确定性的两阶段随机规划方法的有效性与经济性。

A Two-Stage Stochastic Programming Method for Multi-Energy Microgrid System Considering the Uncertainty of New Energy and Load

Aiming at the uncertainty of new energy and load， the quantile gradient boosting regression tree （QGBRT） combined with chance constrained programming method based on quantile-confidence interval prediction is proposed， and a two-stage stochastic scheduling optimization model based on energy hub is established. In the form of confidence interval， the method can reflect the adjustable margin of the unit commitment from the statistical level， and provide reliable reference for intraday and real-time dispatching. In the QGBRT prediction method， pinball function describing uncertainty is used as the loss function， and prediction results are used as the constraint information of chance constrained programming. At the same time， in order to make full use of the constantly updated information and relieve the pressure of intraday scheduling plan， in the first stage of the day， according to the published information， the start and stop states of all devices and trading energy state in the microgrid are determined. In the second stage of the day， according to the updated information， the equipment outputs on the basis of the first stage are adjusted and optimized to achieve the accurate and optimal scheduling， which is applicable to actual scheduling. Finally， a typical residential area with multi-energy system is taken as an example to verify the effectiveness and economy of the two-stage stochastic programming method.