基于日间日内不确定集的中长期电源扩展规划

Long-term Generation Expansion Planning Model Based on Intraday and Interday Renewable Energy Uncertainty Sets

电源扩展规划(generation expansion planning,GEP)模型常用于为高比例可再生能源电力系统设计可行的规划方案,而对波动性可再生能源(variable renewable energy,VRE)不确定性的合理表征对规划方案的可行性至关重要。随着风光等可再生能源渗透率的增加,波动性可再生能源表现出了不同时间尺度上的不确定性。提出了一种基于日间和日内可再生能源不确定集的长期GEP模型,从而保障不同时间尺度下的电力电量平衡需求。日间不确定集用来描述长期VRE出力的波动性和间歇性,而日内不确定集用作描述日内的典型和极端出力情形,二者共同描述不同时间尺度下VRE出力的不确定性。使用我国电力系统作为算例,将所提方法与典型日法、典型日聚合法和日间电量平衡法进行仿真对比。基于8760 h全年时序生产模拟的结果表明,所提方法能够显著降低不同风光出力情形下电力系统的失负荷和碳排放,但其他方法均无法满足平衡和清洁需求。

Generation expansion planning(GEP)models are used to find feasible solutions for power systems with high renewable energy shares,and effective planning requires appropriate variable renewable energy(VRE)uncertainty representations.As the VRE penetration increases,VRE uncertainties challenge power systems at different time scales.This article proposes a long-term GEP model based on interday and intraday VRE uncertainty sets that can ensure the electricity balance at different time scales.VRE fluctuation and intermittency are modeled via interday uncertainty sets,while daily typical and extreme VRE outputs are modeled by intraday sets.The effectiveness of the proposed model is validated in China’s power system compared to the representative day method,time series aggregation method,and daily electricity balance method.Lower load loss and carbon emissions are achieved by the proposed method under different 8760-hour VRE outputs but cannot be met by other methods mentioned above.