Multi-stage fully adaptive distributionally robust unit commitment for power system based on mixed approximation rules

Mao Liu, Xiangyu Kong, Chao Ma, Xuesong Zhou and Qingxiang Lin

Applied Energy, 2024, vol. 376, issue PA, No S030626192401434X

Abstract: The escalating integration of renewable energy sources necessitates enhanced power system flexibility. Gas units, with their rapid start-stop capabilities, emerge as crucial assets for system operators grappling with supply-demand fluctuations. This paper proposes a novel multi-stage fully adaptive distributionally robust unit commitment (MFA-DRUC) model to optimize the operation of these flexible units under the uncertainties inherent in real-time dispatch. Leveraging the Wasserstein metric, our approach significantly expands the feasible solution space compared to traditional multi-stage adaptive unit commitment (MA-DRUC) models, bolstering resilience against extreme scenarios. To overcome the computational challenges posed by the model's multi-stage structure, we introduce a mixed approximation rule (MAR) that effectively handles high-dimensional variables and strong coupling characteristics. By employing duality theory, we transform the unit commitment (UC) problem into a computationally tractable mixed-integer linear programming problem. Comprehensive simulations across power systems of varying scales, encompassing scenarios such as coal-fired unit decommissioning and gas unit integration, validate the efficacy of our proposed MFA-DRUC model. These results underscore its potential to enhance the reliability and efficiency of power systems navigating the complexities of a renewables-driven future.

Keywords: Multi-stage Distributionally robust unit commitment; Mixed approximation rule; Data-driven; Dual theory; Sequential decision-making (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.124051

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