Open AccessProbabilistic adaptive model predictive power pinch analysis (PoPA) energy management approach to uncertainty
Author(s) -
Bassey Etim NyongBassey,
Giaouris Damian,
Patsios Haris,
Gadoue Shady,
Papadopoulos Athanasios I.,
Seferlis Panos,
Voutetakis Spyros,
Papadopoulou Simira
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.8154
Subject(s) - probabilistic logic , model predictive control , energy management , monte carlo method , time horizon , computer science , mathematical optimization , power (physics) , control theory (sociology) , constraint (computer aided design) , energy (signal processing) , mathematics , control (management) , statistics , artificial intelligence , physics , geometry , quantum mechanics
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.