Browsing by Author "Fan, Denis"

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    Advanced Occupancy Sensing for Energy Efficiency in Office Buildings
    (Sage, 2016-02-02) Ekwevugbe, Tobore; Brown, Neil; Pakka, V. H.; Fan, Denis
    Control systems for Heating, Ventilation and Air-conditioning (HVAC) in non-domestic buildings often operate to fixed schedules, assuming maximum occupancy during business hours. Since lower occupancies usually mean less demand for HVAC, energy savings could be made. Air quality sensing, often combined with temperature sensing, has performed sufficiently in the past for this if maintained properly, although sensor and control failures may increase energy use by as much as 50%. As energy costs increase, building controls must meet increasingly stringent environmental requirements, increases in building services complexity, and reduced commissioning time, all placing ever higher demands on sensing, with a standing requirement to improve reliability. Sensor fusion offers performance and resilience to meet these demands, while cost and privacy are key factors which are also met. This paper describes a neural network approach to sensor fusion for occupancy estimation. Feature selection was carried out using symmetrical uncertainty analysis, while fusion of sensor features used a back-propagation neural network, with occupant count accuracy exceeding 74%.
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    Exploring Smart Grid Possibilities: A Complex Systems Modelling Approach
    (De Gruyter, 2015-08-26) Rylatt, R. Mark; Snape, J. Richard; Allen, P.; Ardestani, B. M.; Boait, Peter John; Boggasch, E.; Fan, Denis; Fletcher, G.; Gammon, Rupert; Lemon, Mark; Pakka, V. H.; Savill, M.; Smith, Stefan; Strathern, M.; Varga, Liz
    Smart grid research has tended to be compartmentalised, with notable contributions from economics, electrical engineering and science and technology studies. However, there is an acknowledged and growing need for an integrated systems approach to the evaluation of smart grid initiatives. The capacity to simulate and explore smart grid possibilities on various scales is key to such an integrated approach but existing models – even if multidisciplinary – tend to have a limited focus. This paper describes an innovative and flexible framework that has been developed to facilitate the simulation of various smart grid scenarios and the interconnected social, technical and economic networks from a complex systems perspective. The architecture is described and related to realised examples of its use, both to model the electricity system as it is today and to model futures that have been envisioned in the literature. Potential future applications of the framework are explored, along with its utility as an analytic and decision support tool for smart grid stakeholders.
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    Improved occupancy monitoring in non-domestic buildings
    (Elsevier, 2017-01-29) Ekwevugbe, Tobore; Brown, Neil; Pakka, V. H.; Fan, Denis
    Measuring occupancy can facilitate energy efficiency in non-domestic buildings, when control systems are able to adjust heating and cooling based on demand rather than fixed schedules. The variable “occupancy profile” itself is rarely considered as a control system parameter in building energy management systems (BEMS), and this is largely because reliably measuring occupancy in the past has been too difficult, expensive, or a mixture of both. Occupancy detection is possible using e.g. CO2 sensors, passive infra-red (PIR) detectors, which can provide a basic trigger for services, but the actual occupancy count, and therefore the expected load on building services, requires a step change in instrumentation. Advanced occupancy sensors developed from a heterogeneous multisensory fusion strategy offer this, improving control system performance, e.g. turning off services out of hours, and not over-ventilating, saving energy, while not under-ventilating during occupancy, benefitting comfort and health. While this is the case, there is a shortage of any systematic methodology for developing robust and reliable occupancy monitoring systems from heterogeneous multi-sensory sources. In this paper we describe an innovative sensor fusion approach utilising symmetrical uncertainty (SU) analysis and a genetic based feature selection for building occupancy estimation.
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    Using indoor climatic measurements for occupancy monitoring
    (2012) Ekwevugbe, Tobore; Brown, Neil; Fan, Denis