Probabilistic adaptive model predictive power pinch analysis (PoPA) energy management approach to uncertainty

Nyong-bassey Bassey Etim, Damian Giaouris, Haris Patsios, Shady Gadoue, Athanasios I. Papadopoulos, Panos Seferlis, Spyros Voutetakis, Simira Papadopoulou

Research output: Contribution to journalArticle

Abstract

This paper proposes a probabilistic power pinch analysis (PoPA) approach based on Monte–Carlo simulation (MCS)
for energy management of hybrid energy systems uncertainty. The systems power grand composite curve is formulated with the
chance constraint method to consider load stochasticity. In a predictive control horizon, the power grand composite curve is
shaped based on the pinch analysis approach. The robust energy management strategy effected in a control horizon is inferred
from the likelihood of a bounded predicted power grand composite curve, violating the pinch. Furthermore, the response of the
system using the energy management strategies (EMS) of the proposed method is evaluated against the day-ahead (DA) and
adaptive power pinch strategy.
Original languageEnglish
Pages (from-to)4288-4292
JournalThe Journal of Engineering
Volume2019
Issue number17
Early online date4 Apr 2019
DOIs
Publication statusPublished - 17 Jun 2019

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Energy management
Composite materials
Uncertainty

Bibliographical note

This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License
(http://creativecommons.org/licenses/by-nc-nd/3.0/)

Cite this

Bassey Etim, N., Giaouris, D., Patsios, H., Gadoue, S., Papadopoulos, A. I., Seferlis, P., ... Papadopoulou, S. (2019). Probabilistic adaptive model predictive power pinch analysis (PoPA) energy management approach to uncertainty. The Journal of Engineering , 2019(17), 4288-4292. https://doi.org/10.1049/joe.2018.8154
Bassey Etim, Nyong-bassey ; Giaouris, Damian ; Patsios, Haris ; Gadoue, Shady ; Papadopoulos, Athanasios I. ; Seferlis, Panos ; Voutetakis, Spyros ; Papadopoulou, Simira. / Probabilistic adaptive model predictive power pinch analysis (PoPA) energy management approach to uncertainty. In: The Journal of Engineering . 2019 ; Vol. 2019, No. 17. pp. 4288-4292.
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abstract = "This paper proposes a probabilistic power pinch analysis (PoPA) approach based on Monte–Carlo simulation (MCS)for energy management of hybrid energy systems uncertainty. The systems power grand composite curve is formulated with thechance constraint method to consider load stochasticity. In a predictive control horizon, the power grand composite curve isshaped based on the pinch analysis approach. The robust energy management strategy effected in a control horizon is inferredfrom the likelihood of a bounded predicted power grand composite curve, violating the pinch. Furthermore, the response of thesystem using the energy management strategies (EMS) of the proposed method is evaluated against the day-ahead (DA) andadaptive power pinch strategy.",
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Bassey Etim, N, Giaouris, D, Patsios, H, Gadoue, S, Papadopoulos, AI, Seferlis, P, Voutetakis, S & Papadopoulou, S 2019, 'Probabilistic adaptive model predictive power pinch analysis (PoPA) energy management approach to uncertainty', The Journal of Engineering , vol. 2019, no. 17, pp. 4288-4292. https://doi.org/10.1049/joe.2018.8154

Probabilistic adaptive model predictive power pinch analysis (PoPA) energy management approach to uncertainty. / Bassey Etim, Nyong-bassey; Giaouris, Damian; Patsios, Haris; Gadoue, Shady; Papadopoulos, Athanasios I.; Seferlis, Panos; Voutetakis, Spyros; Papadopoulou, Simira.

In: The Journal of Engineering , Vol. 2019, No. 17, 17.06.2019, p. 4288-4292.

Research output: Contribution to journalArticle

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AU - Papadopoulos, Athanasios I.

AU - Seferlis, Panos

AU - Voutetakis, Spyros

AU - Papadopoulou, Simira

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Bassey Etim N, Giaouris D, Patsios H, Gadoue S, Papadopoulos AI, Seferlis P et al. Probabilistic adaptive model predictive power pinch analysis (PoPA) energy management approach to uncertainty. The Journal of Engineering . 2019 Jun 17;2019(17):4288-4292. https://doi.org/10.1049/joe.2018.8154