Computational BIPV Design: An Energy Optimization Tool for Solar Façades
In contemporary buildings, façades are generally the largest borders between the inside and the outside which determine the proportion of energy consumption of the buildings. With today’s technology, they could also offer the opportunity of producing energy by adding photovoltaics into their systems, to cover a portion of the building’s need for electricity and reduce its dependency on fossil fuels, especially where there is a high amount of global horizontal irradiation (GHI) and a high potential for generating electricity from photovoltaics. In the new concepts, building-integrated photovoltaics (BIPV) is even being used in the transparent sections of the façades which should be a cautious decision as they can highly affect the total energy demand of the building due to the change in the proportion of daylight and heat that can pass through. Thus, they should all be taken into consideration during the first stages of design to get the best result possible. While there have been some studies on this subject, we are still facing a shortage of tools and methods for BIPV design in the preliminary design phases.
This research aimed to provide a design tool for BIPV systems by making use of the integration of energy simulation programs with visual programming tools to spot the best façade solutions for any specific project. The optimization of these solar façades by this tool is discussed and compared to the nonoptimized alternatives. To put it briefly, the tests were done on a common vertical two-section façade with windows to provide natural light and solar heat to a certain amount that would be beneficial energy-wise, with crystalline silicon-based photovoltaics in the remaining parts of the façades.
The simulation results illustrated how a great quantity of inputs could affect the performance to a great extent. For instance, glazing material was put on a test and the results with four different alternatives in the south façade of Cairo (Egypt) showed that a wrong decision on glazing material alone could result in an increase of 28% in lower window-to-wall ratios (WWRs) and 51% in higher WWRs in the energy consumption of an office room. Therefore, by choosing the optimal solution for each input, we could reduce the energy use of a building extensively which highlights the need for tools to come to the aid of the decision makers to find the best options and avoid choosing the inferior alternatives during the first stages of design.
KeywordsEnergy optimization tool Building-integrated photovoltaics (BIPV) Solar façades Passive design
- 2.Lobaccaro G, Fiorito F, Masera G, Prasad D (2012) Urban solar district: a case study of geometric optimization of solar facades for a residential building in Milan. In: International conference “Solar 2012”, Melbourne. December 2012Google Scholar
- 3.Lovati M (2014) A BiPV design optimization method. In: International conference SOLARTR 2014, Izmir, November 2014Google Scholar
- 4.Robinson L, Athienitis A (2009) Design methodology for optimization of electricity generation and daylight utilization for façade with semitransparent photovoltaics. In: Proceedings of building simulation 2009: 11th international IBPSA conference Glasgow, Scotland, pp 811–818Google Scholar
- 5.Sandra M, Frontini F, Wienold J (2011) Comfort and building performance analysis of transparent building integrated silicon photovoltaics. In: Proceedings of building simulation 2011: 12th conference of international building performance simulation association, Sydney, pp 2080–2087Google Scholar
- 6.Goldberg DE (1989) Genetic algorithms in search optimization and machine learning. University of Alabama, Addison WesleyGoogle Scholar
- 8.EN 12464-1:2011. Light and lighting – lighting of work places – Part 1: Indoorwork places. European Committee for Standardization (CEN), 2011Google Scholar
- 9.EnergyPlus. Version 8.1. 2013. Engineering Reference The Reference to EnergyPlus Calculations. Lawrence Berkeley, National Laboratory, 2013Google Scholar
- 10.RADIANCE, the radiance 4.0 synthetic imaging system (2010) Lawrence Berkeley, National Laboratory, Berkeley,Google Scholar
- 11.Roy GG (2000) A Comparative Study of Lighting Simulation Packages Suitable for use in Architectural Design. Murdoch University. PerthGoogle Scholar