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计及惯量和风电双重不确定性的两阶段分布鲁棒机组组合
Two-Stage Distributionally Robust Unit Commitment Considering Dual Uncertainties of Inertia and Wind Power
【目的】针对高比例新能源渗透率下电网惯量来源多元化和不确定性所导致的系统频率响应能力不足，提出一种在机组组合中考虑惯量来源多元化以及惯量和风电不确定性的方法。【方法】首先，综合调度部门所掌控的同步发电机组惯量、不被调度部门掌控的小型同步发电机组惯量、虚拟惯量和负荷侧惯量，建立惯量不确定性模型。其次，采用基于数据驱动的两阶段分布鲁棒优化模型刻画惯量和风电的双重不确定性，并用1-范数及∞-范数约束不确定性概率分布置信集合，同时在第二阶段模型中考虑动态频率约束。最后，将模型中含有绝对值的部分线性化，采用列与约束生成算法对两阶段模型求解。【结果】相较于仅考虑大型同步发电机惯量的机组组合模型，所提模型具有更充足的频率响应能力，且发电总成本降低了3.3%。【结论】与其他不确定性方法相比，所构建的模型有更好的经济性，相较于随机优化模型有更强的鲁棒性，有效平衡了电力系统经济性与鲁棒性之间的关系，从而确保系统在可再生能源高渗透场景下具备动态适应能力。
[Objective] To address the insufficient system frequency response capability caused by the diversification and uncertainty of grid inertia under high renewable energy penetration，this paper proposes a method for unit commitment that considers diverse inertia sources as well as the uncertainties associated with inertia and wind power. [Methods] First，an inertia uncertainty model is established by integrating various inertia sources，including synchronous generator inertia controlled by the dispatch center，inertia from small-scale synchronous generators not directly controlled by the dispatch center，virtual inertia，and demand-side inertia. Second，a data-driven two-stage distributionally robust optimization （DRO） model is formulated to characterize the dual uncertainties of inertia and wind power. The 1-norm and ∞-norm are utilized to constrain the confidence set of uncertain probability distributions. Meanwhile，dynamic frequency constraints are incorporated into the second-stage model. Finally，the absolute value terms within the model are linearized，and the Column-and-Constraint Generation （C&CG） algorithm is employed to solve the two-stage model. [Results] Compared with the unit commitment model considering only the inertia of large synchronous generators，the proposed two-stage DRO model，which accounts for the dual uncertainties of inertia and wind power，demonstrates superior frequency response capability and reduces the total generation cost by 3.3%. [Conclusions] Compared with other uncertainty-handling methods，the constructed model achieves better economic efficiency than robust optimization models and enhanced robustness compared to stochastic optimization models. It effectively balances the relationship between economic efficiency and robustness，thereby ensuring the power system's dynamic adaptability under high renewable energy penetration scenarios.
系统惯量 / 不确定性 / 动态频率约束 / 机组组合 / 分布鲁棒优化
system inertia / uncertainty / dynamic frequency constraint / unit combination / distributionally robust optimization
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The inertia reduction caused by the integration of large-scale wind power, PV, and other renewable energy sources has brought new challenges to the safe operation of new type power systems, especially transient frequency safety. In this paper, on the basis of making full use of the frequency support of new energy sources, a two-layer optimization strategy for unit combinations with transient frequency constraints is proposed. A new frequency-response model of the power system considering the frequency support of the new energy station is constructed, and the analytical expression of the transient frequency characteristic quantity is deduced. Then, on the basis of the traditional unit combination model, a unit combination optimization model considering the dynamic frequency constraint is constructed. Introducing an atomic search algorithm, synergistically considering frequency support for optimal load shedding optimization of new energy sources, and unit combination optimization, a two-layer optimization strategy is established. Taking a 10-machine system including PV and wind power as an example, the calculation and analysis are carried out, and the results verify the effectiveness and feasibility of the method in this paper. |
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为降低源荷两侧不确定性对综合能源系统(integrated energy system, IES)安全性与经济性的影响，以及提升IES面对不确定性的灵活、稳定运行的能力，提出多种储能参与平抑不确定性波动的策略，建立多重不确定性下日前-实时两阶段协同优化的鲁棒模型。模型中加入鲁棒可调因子综合评估系统经济性与鲁棒性，在日前阶段，根据新能源及负荷预测功率确定预调度计划，以实现最小运行成本下的功率平衡；在实时阶段，根据新能源出力及负荷实际模拟功率确定参与二次灵活调整设备的调整功率，以最小成本实现功率再平衡。算例表明，电源侧、储能侧的实时调整能更好发挥IES应对不确定性的协同调节功能；引入鲁棒可调因子刻画不确实性，较好地均衡了系统运行的经济性和安全性。
In order to reduce the influence of uncertainty on both sides of the source and load on the security and economy of the integrated energy system (IES), and to improve the flexibility and stability of IES in the face of uncertainties, various strategies for energy storage participation in smoothing out the uncertainty fluctuations are proposed, and a robust model is established for the day-ahead and real-time two-stage cooperative optimization under multiple uncertainties. A robust adjustable factor is added to the model to comprehensively evaluate the system economy and robustness. In the day-ahead phase, a pre-dispatch plan is determined based on the predicted power of new energy and load to realize the power balance at the minimum operating cost. In the real-time phase, the adjustment power of the secondary flexible adjustment equipment is determined according to the new energy output and the actual simulated power of the load to realize power rebalancing at minimum cost. The case study shows that the real-time adjustment of power supply side and energy storage side can better play the synergistic adjustment function of IES to deal with uncertainty; the introduction of robust adjustable factor to portray the uncertainty better balances the economy and security of system operation. |
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