Intelligent Energy Buildings (KAPLANI_U17SCI)

University of East Anglia - School of Mathematics

Start Date: October 2017

Closes:  1st December 2016

No. of positions available: 1

Supervisor: Dr Eleni Kaplani

Project description: The need for reduction in the energy consumption of buildings worldwide has lead to increasing research interest in Zero Energy Buildings (ZEB) and further in Intelligent Energy Buildings (IEB) [1-4]. Reduction in the energy demand may be achieved through passive solar design, novel materials and technologies, highly efficient appliances and change of user consumption behaviour. Building integrated renewable energy systems, including BIPV, PV/T, solar thermal collectors, combined with other technologies such as heat pumps and storage, may cover the power and heat loads required on an annual basis. The optimization of both energy consumption and energy supply contributes further to cost-effective ZEB and IEB configurations.

This PhD project will investigate the stochastic behaviour of the energy consumption in buildings on different time frames and the stochastic energy delivered by the integrated RES, with reference to meteorological parameters at the site. Simulation algorithms will be developed based on the dynamic energy balance of the building with emphasis on the prediction of solar irradiance and the energy delivered by the integrated RES. Optimization techniques for the cost-effective sizing of the integrated RES and the intelligent management of loads will be investigated within the scope of IEB. The simulation algorithms will be tested with measured data obtained from an existing energy building at the University of East Anglia.

Interviews will take place between 16 January and 24 February 2017.

Person specification: Applicants must have a 1st or 2.1 (or equivalent) undergraduate degree in Electrical, Electronic, Mechanical or Energy Engineering or related discipline. An MSc degree in one of these subject areas is desirable but not necessary. Experience in a computer programming language is essential. Experimental work with sensors is desirable.

Funding notes: This PhD project is in a Faculty of Science competition for funded studentships. These studentships are funded for 3 years and comprise home/EU fees, an annual stipend of £14,296 and £1000 per annum to support research training. Overseas applicants may apply but they are required to fund the difference between home/EU and overseas tuition fees (in 2016/17 the difference is £12,879 for the Schools of CHE & PHA, and £9,679 for CMP & MTH but fees are subject to an annual increase)

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