基于风电出力概率预测模型的源荷储日前概率优化调度

Day-ahead probabilistic optimal dispatching of source-load-storage based on probabilistic prediction model of wind power output

为提高电力系统应对风电出力不确定性的能力,基于概率优化方法,构建源荷储日前概率优化调度模型,该模型在考虑风电出力概率分布的同时避免了大量场景的生成与缩减过程,且能够考虑风电出力偏离预测值后常规机组的调整情况,实现备用容量在各机组间的最优分配。在对储能设备进行日前调度时,根据荷电状态的变化动态调整储能设备的充放电功率上限值,改进储能设备的数学模型,避免储能设备发生过充和过放。采用IEEE 6节点系统进行算例分析,验证了所建模型的有效性。

In order to improve the ability of power system to cope with the uncertainty of wind power output,a day-ahead probabilistic optimal dispatching model of source-load-storage is constructed based on the probabilistic optimization method,which avoids the generation and reduction of a large number of scenarios while considering the probabilistic distribution of wind power output,and can consider the adjustment condition of conventional units after deviation of wind power output from the predicted value to achieve the optimal allocation of reserve capacity among each unit.When the day-ahead dispatching of energy storage equipment is carried out,the upper limit of charging and discharging power of energy storage equipment is dynamically adjusted according to the variation of the state of charge,and the mathematical model of the energy storage equipment is improved to avoid overcharging and overdischarging of energy storage equipment.The IEEE 6-bus system is adopted for case analysis to verify the validity of the constructed model.