Résumé
Building sector accounts for nearly 40% of the global energy consumption. Energy-hub is attached attentions for the energy/cost saving and load shifting of building. In this paper, we proposed a model predicted control (MPC) based demand-side building energy management framework in the energy-hub structure. Simulations in four scenarios with dynamic electricity price were conducted on a building to investigate the energy saving potential under the proposed framework. In scenario 1 and 2, building climate control and economic control were employed to track the indoor temperature setpoint and minimize the cost respectively. In the scenario 3, a typical demand response problem with electric storage device was studied while an additional on-site generation component was considered in scenario 4. The results demonstrate that scenario 2 can achieve 21% cost saving compared to scenario 1. Furthermore, scenario 3 and 4 can achieve nearly 20% and 31% cost saving compared to scenario 2.
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Détails
- Titre original : Building energy management in energy-hub manner based on economic model predictive control.
- Identifiant de la fiche : 30026662
- Langues : Anglais
- Sujet : Chiffres, économie, Environnement
- Source : Proceedings of the 25th IIR International Congress of Refrigeration: Montréal , Canada, August 24-30, 2019.
- Date d'édition : 24/08/2019
- DOI : http://dx.doi.org/10.18462/iir.icr.2019.0908
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Indexation
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Formulation and application of an economic mode...
- Auteurs : ELLIS M. J., ALANQAR A.
- Date : 09/07/2018
- Langues : Anglais
- Source : 2018 Purdue Conferences. 5th International High Performance Buildings Conference at Purdue.
- Formats : PDF
Voir la fiche
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Pattern analysis of dynamic grid incentives and...
- Auteurs : LI L. X., PAVLAK G. S.
- Date : 24/05/2021
- Langues : Anglais
- Source : 2021 Purdue Conferences. 6th International High Performance Buildings Conference at Purdue.
- Formats : PDF
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Evaluation of the electrical energy consumption...
- Auteurs : DAMIAN A., POPESCU R., BAJENARU N., et al.
- Date : 16/08/2015
- Langues : Anglais
- Source : Proceedings of the 24th IIR International Congress of Refrigeration: Yokohama, Japan, August 16-22, 2015.
- Formats : PDF
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Uncertainty analysis of a heavily instrumented ...
- Auteurs : OSTROUCHOV G., NEW J., SANYAL J., et al.
- Date : 14/07/2014
- Langues : Anglais
- Source : 2014 Purdue Conferences. 3rd International High Performance Buildings Conference at Purdue.
- Formats : PDF
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Machine-learning model of electric water heater...
- Auteurs : DONG J., MUNK J., CUI B., et al.
- Date : 09/07/2018
- Langues : Anglais
- Source : 2018 Purdue Conferences. 5th International High Performance Buildings Conference at Purdue.
- Formats : PDF
Voir la fiche