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Lookup NU author(s): Professor Damian Giaouris, Professor Haris Patsios, Professor Sara Walker, Professor Phil Taylor
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
In this work, we propose a novel, generic and systematic approach of modelling and controlling the assets in a microgrid under multiple stochastic loads. The proposed model inherently accounts for multiple and diverse energy carriers, handles multiple random loads with time dependant importance and supports the use of both load forecasting tools and demand side response strategies. The main modelling concept is based on a state space representation that transforms the power network into a hybrid dynamical system and the implemented energy management strategy into the evolution operator. The model integrates structural, temporal and logical features of smart grid systems in order to identify and construct multiple different energy management strategies which can then be compared with respect to their ability to best serve the considered demands. The proposed modelling approach is used to derive 20 energy management strategies considering both demand side response and forecasting, using data from a real hybrid energy system (built in Greece) which combines renewable sources with electrical energy and hydrogen storage. The obtained results are analysed through a multi-criteria assessment method and compared with a standard energy management strategy, previously proposed and tested in a similar system. The comparison shows that the use of a novel energy management strategy with demand side response enables 28%, 68% and 50% reduction in the use of the back-up, fossil-based generator, the electrolyser and the fuel cell, while maintaining the battery state of charge within a desired operational range over a period of one year.
Author(s): Giaouris D, Papadopoulos A, Patsios C, Walker S, Ziogou C, Taylor P, Voutetakis S, Papadopoulou S, Seferlis P
Publication type: Article
Publication status: Published
Journal: Applied Energy
Year: 2018
Volume: 226
Pages: 546-559
Print publication date: 15/09/2018
Online publication date: 14/06/2018
Acceptance date: 27/05/2018
Date deposited: 08/06/2018
ISSN (print): 0306-2619
Publisher: Elsevier
URL: https://doi.org/10.1016/j.apenergy.2018.05.113
DOI: 10.1016/j.apenergy.2018.05.113
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