在含高比例可再生能源的电力系统中,考虑多重不确定性因素并实现源荷协调的优化调度是电力系统运行的重要问题.为此,构建了基于多场景的概率性旋转备用优化模型,该模型综合考虑了风电和光伏出力预测误差、负荷预测误差及发电机非计划停运等多重不确定性因素对旋转备用容量的影响,将可再生能源弃电、系统切负荷分别作为特殊的备用资源融入发电日前调度计划,以提高电力系统的经济运行效率.改进了系统可再生能源削减期望和电量不足期望值两个可靠性指标的计算方法,减少了与该指标相关的不等式约束条件,用于提升模型的计算性能.该备用优化模型在兼顾场景多样性的同时,实现了多场景下系统的总成本最优.以改进的IEEE-RTS系统作为算例,验证了所提模型的有效性.算例结果表明,改进的可靠性指标计算方法能够有效降低备用优化模型的求解时间;建立的最优旋转备用优化方法能够实现系统日前旋转备用容量的动态配置,提升系统经济运行水平.

In power systems with a high proportion of renewable energy, to achieve coordinated optimal scheduling of source and load considering multiple uncertainties is an important issue in power system operation. Therefore, a probabilistic spinning reserve optimization model based on multiple scenarios is constructed. Multiple uncertain factors are considered in the model, such as wind power and solar power forecast errors, load forecast error and unscheduled generator outage. Renewable energy curtailment and load shedding are used as special reserve resources in the day-ahead security-constrained unit commitment (SCUC) to improve the economic operation efficiency. The calculations of reliability indexes, expected energy not served and expected energy curtailment, are simplified, and the inequality constraints related to these two indexes are reduced, which improves the computational performance of the model. The model optimizes the total expected cost considering multiple uncertainties. Case studies based on the IEEE-RTS demonstrate the effectiveness of the proposed model. The numerical results show that the improved calculation method of reliability indexes can effectively reduce the solution time of the SCUC model. The reserve optimization model can realize the dynamic allocation of the spinning reserve capacity of the system and improve economic operation of the system.