考虑预测误差与频率响应的随机优化调度

Stochastic Optimal Dispatching Considering Prediction Error and Frequency Response

风电能源接入电网的比例不断提高,给电网调度带来了巨大的挑战。传统的调度方法无法有效地处理大规模风电的随机性和系统调频能力变弱的问题。针对大规模风电接入的问题,提出了基于预测误差分布的风功率随机性分析法,通过历史数据对风功率区间进行划分,得到每个区间风功率预测的概率分布,并以此抽样来生成风功率出力场景。通过k-means聚类法对场景进行削减,得到描述风功率随机性的风功率出力场景,并用于随机优化调度中。建立考虑频率响应的随机优化调度模型,在风功率出力误差较大的情况下推导动态频率响应模型,计算频率偏移与系统内常规机组参数的关系式,将其加入到调度模型的约束条件中。在MATLAB中对IEEE-39节点系统进行仿真分析,采用Gurobi求解随机优化调度模型。结果表明提出的方法在大规模风电接入下,能够保证系统的频率稳定和经济运行。

The increasing proportion of wind power connected to the grid has brought a huge challenge to grid dispatching.The traditional dispatching methods cannot effectively deal with the problems of randomness of large-scale wind power and the weakening of the system’s frequency modulation capability.Aiming at this problem,this paper proposes a wind power randomness analysis method based on prediction error distribution.First,the wind power intervals are divided with the historical data to obtain the probability distribution of wind power prediction for each interval,which are sampled to generate wind power output scenarios.Then the k-means clustering method is used to reduce the scenarios to obtain the wind power output scenarios that describe the randomness of wind power,which are used later in the stochastic optimal dispatching.Third,a stochastic optimal dispatching model is established considering the frequency response,which derives a dynamic frequency response model when wind power output errors are large,calculates the relationship between frequency offset and conventional unit parameters in the system,and adds it to the constraints of the dispatching model.Finally,the IEEE-39 node system is simulated and analyzed in MATLAB,and the Gurobi is used to solve the stochastic optimal dispatching model.The result shows that the proposed method in this paper can ensure the frequency stability and economic operation of the system under large-scale wind power access.