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Development of dynamic predictive management models of BIPV and the loads' stochastic patterns in Intelligent Energy Buildings (KAPLANIE_U18SCI)

Project Description

The need for reduction in the energy consumption of buildings worldwide has lead to increasing research interest in Zero Energy Buildings (ZEB) [1].  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 Photovoltaic (BIPV) systems may cover a fraction of the power loads.  There are ongoing research developments to increase this fraction leading to near-ZEB and ZEB configurations.  New research efforts are directed towards converting the ZEB into Intelligent Energy Building (IEB) [3-4].

This PhD project will develop models for the dynamic prediction of the hourly solar irradiance with its inherent fluctuations and the power produced by the BIPV system.  It will investigate the stochastic behaviour of the hourly power consumption in the building taking into account the meteorological parameters at the site. Optimization techniques for the cost-effective sizing of the BIPV and the intelligent management of the loads will be investigated within the scope of IEB.  The simulation algorithms will be tested with measured data obtained from an existing energy building.

Applicants must have a 1st or 2.1 (or equivalent) undergraduate degree in Electrical, Electronic, Mechanical or Energy Engineering, Physics 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.

Interviews will be held w/c 22 January 2018.

References

i) H. Lund, A. Marszal, P. Heiselberg (2011). Zero energy buildings and mismatch compensation factors. Energy and Buildings, Vol. 43, p.1646-54.

ii) D. Kolokotsa, D. Rovas, E. Kosmatopoulos, K. Kalaitzakis(2011). A roadmap towards intelligent net zero- and positive-energy buildings. Solar Energy, Vol. 52, p.3067-84.

iii) T.A. Nguyen, M. Aiello (2013). Energy intelligent buildings based on user activity: A survey. Energy and Buildings, Vol. 56, p. 244-57.

iv) S. Kaplanis, E. Kaplani (Eds.)(2013). Renewable Energy Systems: Theory, Innovations and Intelligent Applications. Nova Science Publishers, N.Y.


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Information

  • Start date: October 2018
  • Programme: PhD
  • Mode of Study: Full Time
  • Studentship Length: This studentship is funded for 3 years

How to Apply

Fees & Funding

  • Funding Status: Competition Funded Project (EU Students Only)
    Further Details
  • Funding Conditions:

    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 £14,553 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 2017/18 the difference is £13,805 for the Schools of CHE ,PHA & MTH (Engineering), and £10,605 for CMP & MTH but fees are subject to an annual increase).

  • Fees: Fees Information (Opens in new window)

Entry Requirements

  • Acceptable First Degree:

    Applicants must have an undergraduate degree in Electrical, Electronic, Mechanical or Energy Engineering, Physics or related discipline.

  • Minimum Entry Standard: The standard minimum entry requirement is 2:1.