Issue |
E3S Web Conf.
Volume 111, 2019
CLIMA 2019 Congress
|
|
---|---|---|
Article Number | 06014 | |
Number of page(s) | 8 | |
Section | Sustainable Urbanization and Energy System Integration | |
DOI | https://doi.org/10.1051/e3sconf/201911106014 | |
Published online | 13 August 2019 |
A methodology for designing decentralised energy systems with predictive control for heat pumps and thermal storage
University of Strathclyde, ESRU, 16 Richmond St., Glasgow, UK
* Corresponding author: andrew.lyden@strath.ac.uk
Decentralised energy systems provide the potential for adding energy system flexibility by separating demand/supply dynamics with demand side management and storage technologies. They also offer an opportunity for implementing technologies which enable sector coupling benefits, for example, heat pumps with controls set to use excess wind power generation. Gaps in this field relating to planning-level modelling tools have previously been identified: thermal characteristic modelling for thermal storage and advanced options for control. This paper sets out a methodology for modelling decentralised energy systems including heat pumps and thermal storage with the aim of assisting planning-level design. The methodology steps consist of: 1) thermal and electrical demand and local resource assessment methods, 2) energy production models for wind turbines, PV panels, fuel generators, heat pumps, and fuel boilers, 3) bi-directional energy flow models for simple electrical storage, hot water tank thermal storage with thermal characteristics, and a grid-connection, 4) predictive control strategy minimising electricity cost using a 24-hour lookahead, and 5) modelling outputs. Contributions to the identified gaps are examined by analysing the sensible thermal storage model with thermal characteristics and the use of the predictive control. Future extensions and applications of the methodology are discussed.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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