In-House Energy Consumption Scheduling Optimisation Model.
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| Title: | In-House Energy Consumption Scheduling Optimisation Model. |
|---|---|
| Authors: | Komasilovs, Vitalijs1 (AUTHOR), Zacepins, Aleksejs1,2 (AUTHOR) aleksejs.zacepins@lbtu.lv, Meitalovs, Jurijs2,3 (AUTHOR), Paura, Liga1,4 (AUTHOR), Stetjuha, Mihails3 (AUTHOR), Varfolomejevs, Andrejs4 (AUTHOR), Salajevs, Vladimirs1 (AUTHOR), Arhipova, Irina1 (AUTHOR) |
| Source: | Energies (19961073). May2026, Vol. 19 Issue 9, p2190. 17p. |
| Subject Terms: | *Constraint programming, *Constraint satisfaction, *Energy consumption, *Mathematical optimization, *Electricity pricing, *Energy management, *Clean energy, *Sensitivity analysis |
| Abstract: | This paper presents an optimisation model for scheduling in-house energy consumption to improve efficiency and sustainability. Focus is on the integration of advanced scheduling techniques to improve the overall performance of the house appliances and energy storage system. The proposed model applies constraint programming and satisfiability (CP-SAT) techniques to analyse complex schedules. A sensitivity analysis was conducted by perturbing key input parameters, including electricity price variations and demand profiles, while tracking output metrics such as total cost, load distribution, and computational performance. The model incorporates real-world constraints, including fluctuating electricity prices and renewable energy availability, to improve efficiency and reduce operational costs. The optimisation of the scheduling task was set for a 36 h time period with time resolutions of 15 min, equal to the electricity price time step. The proposed approach is evaluated through simulation using representative household consumption profiles and real day-ahead electricity prices data. The performance of the proposed CP-SAT model was evaluated, and the model's response to the input parameter change has been analysed. The computational performance and cost outcomes of the proposed CP-SAT approach are comparable to those reported for established HEMS optimisation methods. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 193716086 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: In-House Energy Consumption Scheduling Optimisation Model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Komasilovs%2C+Vitalijs%22">Komasilovs, Vitalijs</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zacepins%2C+Aleksejs%22">Zacepins, Aleksejs</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> aleksejs.zacepins@lbtu.lv</i><br /><searchLink fieldCode="AR" term="%22Meitalovs%2C+Jurijs%22">Meitalovs, Jurijs</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Paura%2C+Liga%22">Paura, Liga</searchLink><relatesTo>1,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Stetjuha%2C+Mihails%22">Stetjuha, Mihails</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Varfolomejevs%2C+Andrejs%22">Varfolomejevs, Andrejs</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Salajevs%2C+Vladimirs%22">Salajevs, Vladimirs</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Arhipova%2C+Irina%22">Arhipova, Irina</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 9, p2190. 17p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Constraint+programming%22">Constraint programming</searchLink><br />*<searchLink fieldCode="DE" term="%22Constraint+satisfaction%22">Constraint satisfaction</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br />*<searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br />*<searchLink fieldCode="DE" term="%22Electricity+pricing%22">Electricity pricing</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+management%22">Energy management</searchLink><br />*<searchLink fieldCode="DE" term="%22Clean+energy%22">Clean energy</searchLink><br />*<searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper presents an optimisation model for scheduling in-house energy consumption to improve efficiency and sustainability. Focus is on the integration of advanced scheduling techniques to improve the overall performance of the house appliances and energy storage system. The proposed model applies constraint programming and satisfiability (CP-SAT) techniques to analyse complex schedules. A sensitivity analysis was conducted by perturbing key input parameters, including electricity price variations and demand profiles, while tracking output metrics such as total cost, load distribution, and computational performance. The model incorporates real-world constraints, including fluctuating electricity prices and renewable energy availability, to improve efficiency and reduce operational costs. The optimisation of the scheduling task was set for a 36 h time period with time resolutions of 15 min, equal to the electricity price time step. The proposed approach is evaluated through simulation using representative household consumption profiles and real day-ahead electricity prices data. The performance of the proposed CP-SAT model was evaluated, and the model's response to the input parameter change has been analysed. The computational performance and cost outcomes of the proposed CP-SAT approach are comparable to those reported for established HEMS optimisation methods. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=193716086 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/en19092190 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 2190 Subjects: – SubjectFull: Constraint programming Type: general – SubjectFull: Constraint satisfaction Type: general – SubjectFull: Energy consumption Type: general – SubjectFull: Mathematical optimization Type: general – SubjectFull: Electricity pricing Type: general – SubjectFull: Energy management Type: general – SubjectFull: Clean energy Type: general – SubjectFull: Sensitivity analysis Type: general Titles: – TitleFull: In-House Energy Consumption Scheduling Optimisation Model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Komasilovs, Vitalijs – PersonEntity: Name: NameFull: Zacepins, Aleksejs – PersonEntity: Name: NameFull: Meitalovs, Jurijs – PersonEntity: Name: NameFull: Paura, Liga – PersonEntity: Name: NameFull: Stetjuha, Mihails – PersonEntity: Name: NameFull: Varfolomejevs, Andrejs – PersonEntity: Name: NameFull: Salajevs, Vladimirs – PersonEntity: Name: NameFull: Arhipova, Irina IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19961073 Numbering: – Type: volume Value: 19 – Type: issue Value: 9 Titles: – TitleFull: Energies (19961073) Type: main |
| ResultId | 1 |