Multi-timescale Stochastic Programming with Applications in Power Systems
Fuente:
arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866915441377542144 |
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| author | Zhang, Yihang Sen, Suvrajeet |
| author_facet | Zhang, Yihang Sen, Suvrajeet |
| contents | This paper introduces a multi-timescale stochastic programming framework designed to address decision-making challenges in power systems, particularly those with high renewable energy penetration. The framework models interactions across different timescales using aggregated state variables to coordinate decisions. In addition to Multi-timescale uncertainty modeled via multihorizon trees, we also introduce a "synchronized state approximation," which periodically aligns states across timescales to maintain consistency and tractability. Using this approximation, we propose two instantiation methods: a scenario-based approach and a value function-based approach specialized for this setup. Our framework is very generic, and covers a wide-spectrum of applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_08520 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Multi-timescale Stochastic Programming with Applications in Power Systems Zhang, Yihang Sen, Suvrajeet Optimization and Control 90C15 90C39 90C11 This paper introduces a multi-timescale stochastic programming framework designed to address decision-making challenges in power systems, particularly those with high renewable energy penetration. The framework models interactions across different timescales using aggregated state variables to coordinate decisions. In addition to Multi-timescale uncertainty modeled via multihorizon trees, we also introduce a "synchronized state approximation," which periodically aligns states across timescales to maintain consistency and tractability. Using this approximation, we propose two instantiation methods: a scenario-based approach and a value function-based approach specialized for this setup. Our framework is very generic, and covers a wide-spectrum of applications. |
| title | Multi-timescale Stochastic Programming with Applications in Power Systems |
| topic | Optimization and Control 90C15 90C39 90C11 |
| url | https://arxiv.org/abs/2508.08520 |