计及广义惯量的电力系统动态频率稳定预防控制理论方法

新能源发电的高比例接入将使电力系统惯量降低，频率稳定问题凸显。频率稳定预防控制通过在日前调度模型中加入对惯量的约束，实现动态频率稳定的预防控制。传统方法通常只考虑同步发电机的转动惯量，而近期大量研究表明新能源发电以及需求侧提供的广义惯量将对频率稳定产生显著影响。因此，本项目拟研究广义惯量的波动规律及其不确定性对频率稳定预防控制的影响，首先探索负荷、新能源出力与广义惯量之间的耦合关系，在有限信息下实现系统整体广义惯量的日前预测；其次，通过数据驱动的机会约束规划平衡经济性与频率稳定性的矛盾；最后研究需求侧快速响应对于广义惯量的代替效果，促进需求侧频率资源的优化配置。本项目运用统计学模型与人工智能算法，揭示高比例新能源接入对电力系统惯量波动的影响规律，在此基础上构建一套计及广义惯量的频率稳定预防控制方法，为高比例可再生能源电力系统的经济、安全运行提供理论基础和技术支撑。

The high penetration of intermittent renewable energy sources, which is anticipated in future power systems will undoubtedly cause the system inertia to vary significantly. Any significant fall in the inertia of a system may compromise the operational security issue. The Frequency Dynamics Constrained Unit Commitment (FDCUC) is a measurement to reduce the risk by introducing inertia-related constraints in the unit commitment model. Traditional FDCUC only considers inertia in the form of kinetic energy stored in rotating plants. However, recent studies have demonstrated that synthetic inertia provided by inverter-interfaced energy sources and loads has a significant impact on the dynamic frequency stability of the system. At present, system inertia lies in a relatively narrow range while in the future the aggregated inertia will become highly variable, making it more difficult for FDCUC to balance the trade-off between economic efficiency and frequency stability. This project aims to investigate FDCUC considering the uncertain aggregated inertia through three work packages: i) probabilistic forecasting of synthetic inertia; ii) handling the uncertainty of synthetic inertia by data-driven chance-constrained optimization under Wasserstein ambiguity sets; iii) pricing the demand-side fast frequency response and optimising the portfolio of demand-side resources. The fundamental research of this project is to explore the variable nature of synthetic inertia based on statistical methods and artificial intelligence models, based on which a novel FDCUC model will be developed to include the aggregated inertia. The research will reduce the stability margins and provide more economical exploitation of the system.