Scheduling Electricity Production Units to Mitigate Severe Weather Impact: An Efficient Computational Implementation
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| Format: | Preprint |
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2026
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| _version_ | 1866908936384282624 |
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| author | Dai, Yongzheng Conejo, Antonio J. Qiu, Feng |
| author_facet | Dai, Yongzheng Conejo, Antonio J. Qiu, Feng |
| contents | In the electric system, extreme weather events can cause trips or physical damage to transmission lines, leading to large-scale load shedding. To mitigate power shedding, we propose a framework that pre-positions the commitment of production units--particularly slow-start units--to cope with transmission topologies that may result from such events. Our goal is to minimize load shedding under the worst-case scenario. The novel contributions of this paper are twofold: (1) a more precise description of the physical laws than those used in previous works reported in the literature, and (2) a highly efficient solution algorithm compared to state-of-the-art, off-the-shelf solvers. We formulate this framework as a two-stage robust optimization model. In the first stage, generation units are scheduled, and in the second stage, power dispatch decisions are made to minimize load shedding under the worst-case scenario. Convexified AC power flow constraints are incorporated to ensure system reliability and security. The resulting formulation is a tri-level mixed-integer nonlinear optimization problem. To address the computational challenges, we propose a problem-specific outer approximation algorithm embedded within a column-and-constraint generation framework. Computational results demonstrate that our model and algorithm can produce solutions within a standard optimality gap in a reasonable time for moderately large instances. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2604_03475 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Scheduling Electricity Production Units to Mitigate Severe Weather Impact: An Efficient Computational Implementation Dai, Yongzheng Conejo, Antonio J. Qiu, Feng Optimization and Control In the electric system, extreme weather events can cause trips or physical damage to transmission lines, leading to large-scale load shedding. To mitigate power shedding, we propose a framework that pre-positions the commitment of production units--particularly slow-start units--to cope with transmission topologies that may result from such events. Our goal is to minimize load shedding under the worst-case scenario. The novel contributions of this paper are twofold: (1) a more precise description of the physical laws than those used in previous works reported in the literature, and (2) a highly efficient solution algorithm compared to state-of-the-art, off-the-shelf solvers. We formulate this framework as a two-stage robust optimization model. In the first stage, generation units are scheduled, and in the second stage, power dispatch decisions are made to minimize load shedding under the worst-case scenario. Convexified AC power flow constraints are incorporated to ensure system reliability and security. The resulting formulation is a tri-level mixed-integer nonlinear optimization problem. To address the computational challenges, we propose a problem-specific outer approximation algorithm embedded within a column-and-constraint generation framework. Computational results demonstrate that our model and algorithm can produce solutions within a standard optimality gap in a reasonable time for moderately large instances. |
| title | Scheduling Electricity Production Units to Mitigate Severe Weather Impact: An Efficient Computational Implementation |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2604.03475 |