Self-Sustainability Assessment for a High Building Based on Linear Programming and Computational Fluid Dynamics

Author:

Oliveira Carlos1ORCID,Baptista José1ORCID,Cerveira Adelaide2ORCID

Affiliation:

1. Departamento de Engenharias, Escola de Ciências e Tecnologia, Universidade de Trás-os-Montes, e INESC-TEC UTAD Pole, 5000-801 Vila Real, Portugal

2. Departamento de Matemática, Escola de Ciências e Tecnologia, Universidade de Trás-os-Montes, e INESC-TEC UTAD Pole, 5000-801 Vila Real, Portugal

Abstract

With excess energy use from non-renewable sources, new energy generation solutions must be adopted to make up for this excess. In this sense, the integration of renewable energy sources in high-rise buildings reduces the need for energy from the national power grid to maximize the self-sustainability of common services. Moreover, self-consumption in low-voltage and medium-voltage networks strongly facilitates a reduction in external energy dependence. For consumers, the benefits of installing small wind turbines and energy storage systems include tax benefits and reduced electricity bills as well as a profitable system after the payback period. This paper focuses on assessing the wind potential in a high-rise building through computational fluid dynamics (CFD) simulations, quantifying the potential for wind energy production by small wind turbines (WT) at the installation site. Furthermore, a mathematical model is proposed to optimize wind energy production for a self-consumption system to minimize the total cost of energy purchased from the grid, maximizing the return on investment. The potential of a CFD-based project practice that has wide application in developing the most varied processes and equipment results in a huge reduction in the time and costs spent compared to conventional practices. Furthermore, the optimization model guarantees a significant decrease in the energy purchased at peak hours through the energy stored in energy storage systems (ESS). The results show that the efficiency of the proposed model leads to an investment amortization period of 7 years for a lifetime of 20 years.

Funder

National Funds through the Portuguese funding agency

Publisher

MDPI AG

Subject

Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science

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4. European Union (2018). Directive 2018/844 of the European Parliament and of the Council of 30 May 2018, amending Directive 2010/31/EU on the energy performance of buildings and Directive 2012/27/EU on energy efficiency. Off. J. Eur. Union, L 156, 75–91. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32018L0844&qid=1628935298304.

5. European Union (2018). Directive 2018/2001 of the European Parliament and of the Council of 11 December 2018 on the promotion of the use of energy from renewable sources. Off. J. Eur. Union, L 328/82, 75. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32018L2001&from=EN.

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