考虑风电功率预测不确定性的日前发电计划鲁棒优化方法

随着风能发电电源并网装机容量的不断升高,风电的强随机性迫使日前发电计划需要购买大量的发电备用,造成全系统发电经济性恶化。在分析风电功率时变预测不确定性的基础上,提出了计及日内现货市场滚动交易的两阶段带补偿鲁棒优化方法。通过在第一阶段日前优化过程中计及日内滚动交易偏差电力的预期,降低了日前发电计划中的备用总需量;对于第二阶段日内调整电力大小的求解,采用了高精度的预测模型,以提升系统发电经济性。最后通过对比分析算例验证了所提方法的正确性和有效性。

Robust Optimization Method for Day-ahead Generation Scheduling Considering Prediction Uncertainty of Wind Power

With the increase of wind power installed capacity, the stochastic behaviours of wind energy pose a great challenge to the day-ahead generation scheduling. Thus a large amount of reserve capacity is needed, which causes economic deterioration of the power system. An improved two-stage robust optimization with recourse method considering the rolling trading of inner-day electricity market is proposed based on the analysis of time-varying prediction uncertainty of wind power. In the first stage of day-ahead optimization process, reserve capacity of day-ahead generation scheduling is reduced considering expected power deviation of inner-day rolling trading. In the second stage, prediction model with high precision is used to calculate the inner-day regulated power to improve the economy of the power system. Correctness and effectiveness of the proposed method are verified by contrastive analysis cases.