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Models for heating system optimisation

Research output: Contribution to conference - Without ISBN/ISSN Poster

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Models for heating system optimisation. / Tate, Oliver; Cheneler, David; Taylor, Charles James.

2018. Poster session presented at 12th UKACC International Conference on Control, Sheffield, United Kingdom.

Research output: Contribution to conference - Without ISBN/ISSN Poster

Harvard

Tate, O, Cheneler, D & Taylor, CJ 2018, 'Models for heating system optimisation' 12th UKACC International Conference on Control, Sheffield, United Kingdom, 5/09/18 - 7/09/18, .

APA

Tate, O., Cheneler, D., & Taylor, C. J. (2018). Models for heating system optimisation. Poster session presented at 12th UKACC International Conference on Control, Sheffield, United Kingdom.

Vancouver

Tate O, Cheneler D, Taylor CJ. Models for heating system optimisation. 2018. Poster session presented at 12th UKACC International Conference on Control, Sheffield, United Kingdom.

Author

Tate, Oliver ; Cheneler, David ; Taylor, Charles James. / Models for heating system optimisation. Poster session presented at 12th UKACC International Conference on Control, Sheffield, United Kingdom.

Bibtex

@conference{56b922c7f6a94fdeb23b895db61ca5e6,
title = "Models for heating system optimisation",
abstract = "Heating, Ventilation and Air Conditioning (HVAC) systems generally have high energy requirements, hence there is considerable interest in the development of modelling techniques, optimisation tools and micro-climate control algorithms for buildings. Pertinent to this research area is the Lancaster University Main Campus, for which a central energy centre supplies the hot water used to heat around 50{\%} of the buildings. The Building Management System provides an abundance of energy data for the entire campus, which is further enhanced by the availability of data from the Hazelrigg weather station. This project concerns the development simple, flexible models suitable for improving control system robustness and overall system optimisation. Lancaster's energy centre provides multiple methods of heat production, such as gas boilers and a biomass generator. The models are being used to explore options for hierarchical control, with a focus on optimising the use of the boilers and generator. To achieve this, non-minimal state space model predictive control methods are being adapted for this application. A novelty of the research is the incorporation of weather forecasting and human occupancy data into the control calculations. The research considers the Charles Carter Building as a case study example. This building has a central atrium, surrounded by lecture theatres, offices, meeting rooms and break-out spaces.",
keywords = "Heating, Ventilation and Air Conditioning (HVAC), Building Management System",
author = "Oliver Tate and David Cheneler and Taylor, {Charles James}",
year = "2018",
language = "English",
note = "12th UKACC International Conference on Control ; Conference date: 05-09-2018 Through 07-09-2018",
url = "https://control2018.group.shef.ac.uk/",

}

RIS

TY - CONF

T1 - Models for heating system optimisation

AU - Tate, Oliver

AU - Cheneler, David

AU - Taylor, Charles James

PY - 2018

Y1 - 2018

N2 - Heating, Ventilation and Air Conditioning (HVAC) systems generally have high energy requirements, hence there is considerable interest in the development of modelling techniques, optimisation tools and micro-climate control algorithms for buildings. Pertinent to this research area is the Lancaster University Main Campus, for which a central energy centre supplies the hot water used to heat around 50% of the buildings. The Building Management System provides an abundance of energy data for the entire campus, which is further enhanced by the availability of data from the Hazelrigg weather station. This project concerns the development simple, flexible models suitable for improving control system robustness and overall system optimisation. Lancaster's energy centre provides multiple methods of heat production, such as gas boilers and a biomass generator. The models are being used to explore options for hierarchical control, with a focus on optimising the use of the boilers and generator. To achieve this, non-minimal state space model predictive control methods are being adapted for this application. A novelty of the research is the incorporation of weather forecasting and human occupancy data into the control calculations. The research considers the Charles Carter Building as a case study example. This building has a central atrium, surrounded by lecture theatres, offices, meeting rooms and break-out spaces.

AB - Heating, Ventilation and Air Conditioning (HVAC) systems generally have high energy requirements, hence there is considerable interest in the development of modelling techniques, optimisation tools and micro-climate control algorithms for buildings. Pertinent to this research area is the Lancaster University Main Campus, for which a central energy centre supplies the hot water used to heat around 50% of the buildings. The Building Management System provides an abundance of energy data for the entire campus, which is further enhanced by the availability of data from the Hazelrigg weather station. This project concerns the development simple, flexible models suitable for improving control system robustness and overall system optimisation. Lancaster's energy centre provides multiple methods of heat production, such as gas boilers and a biomass generator. The models are being used to explore options for hierarchical control, with a focus on optimising the use of the boilers and generator. To achieve this, non-minimal state space model predictive control methods are being adapted for this application. A novelty of the research is the incorporation of weather forecasting and human occupancy data into the control calculations. The research considers the Charles Carter Building as a case study example. This building has a central atrium, surrounded by lecture theatres, offices, meeting rooms and break-out spaces.

KW - Heating, Ventilation and Air Conditioning (HVAC)

KW - Building Management System

M3 - Poster

ER -