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Scalable local energy management systems

Javed, Amir, Rana, Omer F., Cipcigan, Liana M. and Marmaras, Charalampos 2017. Scalable local energy management systems. Energy Procedia 142 , pp. 3069-3074. 10.1016/j.egypro.2017.12.446

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Abstract

Commercial buildings have been identified as a major contributor of total global energy consumption. Mechanisms for collecting data about energy consumption patterns within buildings, and their subsequent analysis to support demand estimation (and reduction) remain important research challenges, which have already attracted considerable work. We propose a cloud based energy management system that enables such analysis to scale to both increasing data volumes and number of buildings. We consider both energy consumption and storage to support: (i) flattening the peak demand of commercial building(s); (ii) enable a “cost reduction” mode where the demand of a commercial building is reduced for those hours when a “triad peak” is expected; and (iii) enables a building manager to participate in grid balancing services market by means of demand response. The energy management system is deployed on a cloud infrastructure that adapts the number of computational resources needed to estimate potential demand, and to adaptively run multiple what-if scenarios to choose the most optimum configuration to reduce building energy demand.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Engineering
Publisher: Elsevier
ISSN: 1876-6102
Funders: EPSRC
Date of First Compliant Deposit: 22 March 2018
Last Modified: 19 Jul 2019 12:59
URI: http://orca.cf.ac.uk/id/eprint/110077

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