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Jones, Sean; Charlesworth, Richard David; Naik, Kevin; Charlesworth, Thomas; O’Dwyer, Edward; Ianakiev, Anton; Johnson, Jeffrey; Boukhanouf, Rabah; Gillott, Mark; Sellwood, Victor and Aloor, Joy
(2021).
DOI: https://doi.org/10.1016/j.egyr.2021.08.159
Abstract
This paper describes a multi-energy system optimisation software, “Sustainable Energy Management System” (SEMS), developed as part of a Siemens, Greater London Authority and Royal Borough of Greenwich partnership in collaboration with the University of Nottingham, Nottingham Trent University and Imperial College London. The software was developed for application at a social housing estate in Greenwich, London, as part of the Borough’s efforts to retrofit the energy systems and building fabric of its housing stock. Its purpose is to balance energy across vectors and networks through day-ahead forecasting and optimisations that can be interpreted as control outputs for energy plant such as a water source heat pump, district heating pumps and values, power switchgear, gas boilers, a thermal store, electric vehicle chargers and a photovoltaic array. The optimisation objectives are to minimise greenhouse gas emissions and operational cost.
The tool uses Hypernetwork Theory based orchestration coupled with a microservice architecture. The distributed nature of the design ensures flexibility and scalability. Currently, microservices have been programmed to forecast domestic heating demand, domestic electricity demand, electric vehicle demand, solar photovoltaic generation, ground temperature, and to run a day-ahead energy balance optimisation. This paper presents the results from both domestic heat and electricity demand forecasting, as well as the overall design and integration of the software with a physical system.
The works build on that of O’Dwyer, et al. (2020) who developed a preliminary energy management software and digital twin. Their work acts as a foundation for this real-world commercialisation-ready program that integrates with physical assets.
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About
- Item ORO ID
- 79861
- Item Type
- Conference or Workshop Item
- ISSN
- 2352-4847
- Project Funding Details
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Funded Project Name Project ID Funding Body Horizon 2020 691895 European Union - Keywords
- Multi-energy systems; Energy optimisation; Predictive algorithm; Hypernetwork theory; Microservice architecture
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation - Copyright Holders
- © 2021 The Authors
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