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A Systems Approach for Management of Microgrids Considering Multiple Energy Carriers, Stochastic Loads, Forecasting and Demand Side Response

Lookup NU author(s): Professor Damian Giaouris, Dr 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.

Publication metadata

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


DOI: 10.1016/j.apenergy.2018.05.113


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