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Optimization of energy performance with renewable energy project sizing using multiple objective functions
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| Veröffentlicht in: | Energy reports 5(2019) vom: Nov., Seite 898-908 |
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| Personen und Körperschaften: | , , , , |
| Titel: | Optimization of energy performance with renewable energy project sizing using multiple objective functions/ E.O.B. Ogedengbe, P.A. Aderoju, D.C. Nkwaze, J.B. Aruwajoye, M.B. Shitta |
| Format: | E-Book-Kapitel |
| Sprache: | Englisch |
| veröffentlicht: |
2019
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| Gesamtaufnahme: |
: Energy reports, 5(2019) vom: Nov., Seite 898-908
, volume:5 |
| Schlagwörter: | |
| Quelle: | Verbunddaten SWB Lizenzfreie Online-Ressourcen |
| Zusammenfassung: | Energy demand profiling of varied stocks within the Faculty of Engineering is investigated, comprising of audit activities like the performance optimization of air-conditioners and other energy appliances. Using a newly-developed renewable energy (RE) calculator, standard energy performance methodologies, including cooling load analysis, energy audit and rating exercises, thermal comfort analysis, distributed power generation from wind turbine and solar photovoltaic module, are adopted. Based on a comprehensive energy audit exercise, areas of energy saving potential are observed. Also, the minimum energy performance standard of energy appliances for maximum human thermal comfort is assessed. Towards the possibility of integrating different sources of renewable energy into the Faculty of Engineering for alternative power supply, an open source widget toolkit based on Qt development environment is used to design a new renewable energy (RE) calculator, known as EnerghxPlus. A multiple objective function approach is proposed to properly evaluate all the key performance indicators simultaneously, thereby unveiling the existing gaps and identifying possible synergies and strategies in the estimation of the building life cycle. The regression of the data obtained from the segregated optimization approach shows a strong linear relationship (i.e., for the appliance audit, the coefficient of determination is approximately 84%; while the correlation coefficient is 0.92). It is anticipated that the application of the proposed methodologies to the multi-scale and multi-objective nature of the challenges in the optimization of energy demand in the built environment will address the uncertainties in previous modelling strategies. |
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| ISSN: |
2352-4847
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| DOI: | 10.1016/j.egyr.2019.07.005 |