数据驱动下基于风电场景的多时间尺度调峰调度研究

风电具有明显的波动性和反调峰特性。为减少风电大规模并网对电力系统调峰带来的影响，提出了一种基于风电调峰场景的多时间尺度调度策略，提高了极端风电场景下电网调度的执行效率。首先，构建了风电-负荷数据驱动模型。提出了风电调峰功率的多时间尺度评估指标，根据该指标对一年的风电功率进行时域分解并生成典型的风电调峰场景。其次，为保证在调峰场景下电网的功率平衡，针对历史场景构建了风火储协同调峰模型，并制定典型场景的经济最优调度预案。在此基础上提出多时间尺度调度策略，通过对调度预案进行滚动修正以应对风电的不确定性。最后，通过算例分析验证了所提方法在保证电网经济稳定运行的前提下可有效地提高调峰调度的计算速度并及时实施调峰调度。

A multi-time scale peak shaving scheduling strategy based on wind power scenario using a data-driven method

Wind power has obvious volatility and anti-peak shaving characteristics. To reduce the impact of large-scale wind power grid connection on power system peak shaving, this paper proposes a multi-time scale scheduling scheme based on wind power peak shaving scenarios. This improves the implementation efficiency of a power grid scheduling scheme in extreme wind power scenarios. First, this paper constructs a wind power load data-driven model, and then a multi-time scale evaluation index of wind power peak shaving power is proposed. From this index, the wind power of a year is decomposed in the time domain and typical wind power peak shaving scenarios are generated for analysis. Second, in order to ensure the power balance of the power grid in the peak shaving scenario, a wind-thermal-energy storage coordinated peak shaving model is built for the historical scenario, and the economic optimal dispatching plan for typical scenarios is formulated. Then a multi-time scale scheduling scheme is proposed to deal with the uncertainty of wind power through rolling revision of the scheduling plan. Finally, the analysis of an example shows that the proposed method can effectively improve the calculation speed of the dispatching scheme and implement the dispatching scheme in time to ensure economic and stable operation of the power grid.