Abstract

Buildings are amongst the world’s largest energy consumers and simultaneous peaks in demand from networks of buildings can decrease electricity system stability. Current mitigation measures either entail wasteful supply-side over-specification or complex centralised demand-side control. Hence, a simple schema is developed for decentralised, self-organising building-to-building load coordination that requires very little information exchange and no top-down management—analogous to other complex systems with short range interactions, such as coordination between flocks of birds or synchronisation in fireflies. Numerical and experimental results reveal that a high degree of peak flattening can be achieved using surprisingly small load-coordination networks. The optimum reductions achieved by the simple schema can outperform existing techniques, giving substantial peak-reductions as well as being remarkably robust to changes in other system parameters such as the interaction network topology. This not only demonstrates that significant reductions in network peaks are achievable using remarkably simple control systems but also reveals interesting theoretical results and new insights which will be of great interest to the complexity and network science communities.

Original languageEnglish
Article number3916
JournalScientific Reports
Volume14
Issue number1
Early online date16 Feb 2024
DOIs
Publication statusPublished - 1 Dec 2024

Data Availability Statement

The data and codes that support the findings of this study are available from the following source: https://bitbu cket.org/apoghosyan/zedip eaksupression/src/master/.

Acknowledgements

With thanks to Dr. Francis Moran and the technicians at the Building Research Park (BRP) for setting up and conducting technical support for the experimental tests.

Funding

This work was funded by the UK Engineering and Physical Sciences Research Council (EPSRC) grant EP/R008612/1 for the project “Zero Peak Energy Building Design for India (ZED-i)”.

FundersFunder number
Engineering and Physical Sciences Research CouncilEP/R008612/1
Engineering and Physical Sciences Research Council

Keywords

  • complex networks, emergent behaviour, bio-inspired design, agent based modelling, Intelligent control, demand side management,

ASJC Scopus subject areas

  • General

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