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Production Scheduling Identification: An Inverse Optimization Approach for Industrial Load Modeling Using Smart Meter Data — arXiv:2608.26485

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.26485
License (as archived): CC0-1.0
Archived: 2026-10-17T22:17:04.418Z
SHA-256 of the archived text: 9542c4f63f3617110e54e3dd7ea85d5116ade7870d6634ebcdb5a135c6a44907
Stable URL of this page: https://metraipolis.com/documento/dc_ce3101ac0b27

How to cite

Production Scheduling Identification: An Inverse Optimization Approach for Industrial Load Modeling Using Smart Meter Data — arXiv:2608.26485 — arXiv (en), https://arxiv.org/abs/2608.26485 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_ce3101ac0b27 (Metraipolis archive dc_ce3101ac0b27, sha256 9542c4f63f3617110e54e3dd7ea85d5116ade7870d6634ebcdb5a135c6a44907)

BibTeX

@misc{dcce3101ac0b27,
  title = {Production Scheduling Identification: An Inverse Optimization Approach for Industrial Load Modeling Using Smart Meter Data — arXiv:2608.26485},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.26485},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_ce3101ac0b27; sha256 9542c4f63f3617110e54e3dd7ea85d5116ade7870d6634ebcdb5a135c6a44907},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.26485. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

To cost-effectively manage the supply-demand balance of the power system, the flexibility of industrial users could be harnessed through demand-side response. To minimize the negative impact on the production of industrial users during demand-side response, general-purpose models such as the state-task network (STN) are widely used to model the energy-consuming constraints of industrial production processes. However, the required model parameters cannot be set because the required data are privately owned by industrial users and are not directly available, hindering the accurate modeling of industrial loads. In this paper, we propose production scheduling identification (PSI), an inverse-optimization-based approach for industrial load modeling under incomplete information. In PSI, industrial users' smart meter data are used to identify production scheduling parameters, thus addressing the problem of accurate load modeling when private data are unavailable. We implemented PSI with a modified STN and proposed a practical algorithm to obtain an effective solution. Numerical tests showed that PSI can identify the model parameters of a steel powder plant and a cement plant with acceptable accuracy, using only 21 days of hourly smart meter data. Compared with accurate models established with direct access to private data, the modeling error does not exceed 8.5% and 5.2%, respectively.

Tema degli esploratori: calcolo e infrastrutture (retro-catalogo arXiv: annunci del 2026-08-28 in eess.SY).
Categorie arXiv: Systems and Control (eess.SY).
Pagina del lavoro: https://arxiv.org/abs/2608.26485 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T22:17:01.621Z dalla pagina https://arxiv.org/catchup/eess.SY/2026-08-28?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).