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Two-Stage Distributionally Robust Unit Commitment Considering Dual Uncertainties of Inertia and Wind Power
ZHANG Lei, SONG Kunze, YE Jing, LIN Yuqi, GAO Renfei
Electric Power Construction ›› 2026, Vol. 47 ›› Issue (2) : 147-160.
PDF(3523 KB)
PDF(3523 KB)
Two-Stage Distributionally Robust Unit Commitment Considering Dual Uncertainties of Inertia and Wind Power
[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.
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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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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