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A Mathematical Programming Approach to Optimal Design of Smart Distributed Energy Systems

Mechleri, Evgenia and Arellano-Garcia, Harvey (2018) A Mathematical Programming Approach to Optimal Design of Smart Distributed Energy Systems In: Computer Aided Chemical Engineering (Part of volume: 13th International Symposium on Process Systems Engineering (PSE 2018)). Elsevier, pp. 2521-2526.

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The UK is committed to reducing its greenhouse gas emissions by at least 80% by 2050, relative to 1990 levels. For this to happen, we need to transform the UK economy while ensuring secure, low-carbon energy supplies to 2050. The future electricity distribution system, known as smart grid, will integrate advanced digital meters, distribution automation, communication systems and distributed energy resources. There has been a lot of discussion about the importance of the Internet of Things (IoT) in future smart grids and smart cities stating that IoT offers many applications and can be used to integrate efficiency renewable energy sources in the smart grid by making the electricity grid more robust and scalable. This study will focus on the development of an integrated IoT-Distributed energy systems (DES) model for the efficient energy management of a microgrid under the integration of the intermittent renewable energy resources. In this work, we expand the definition of flexible options to include demand and supply together with design and operation strategies using internet of things (IoT). Our framework brings weather data and sensor information into a virtual energy plant optimisation model that connects supplier and consumer to optimise potential flexibility gaps arising from supply and demand mismatch. The problem is posed as a hybrid mixed-integer linear programming (MILP) optimisation model combining flexibility analysis and optimal synthesis for integrating energy supply and demand, where environmental information is added to each stage. Finally, we combine traditional mathematical programming approaches such as flexibility analysis and optimal network synthesis and within a single optimisation framework combining IoT and urban DES.

Item Type: Book Section
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
Editors :
Eden, Mario R
Ierapetritou, Marianthi G
Towler, Gavin P
Date : 2 August 2018
DOI : 10.1016/B978-0-444-64241-7.50415-8
Additional Information : Proceedings of the 13th International Symposium on Process Systems Engineering – PSE 2018 July 1-5, 2018, San Diego, California, USA
Depositing User : Melanie Hughes
Date Deposited : 08 Aug 2018 13:30
Last Modified : 15 Nov 2018 12:02

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