Influence of Solar Reflectance and Renewable Energies on Residential Heating and Cooling Demand in Sustainable Architecture: A Case Study in Different Climate Zones in Spain Considering Their Urban Contexts

Abstract

In this research work, energy simulation was used as a forecasting tool in architectural design. It includes the study of a multi-family residential building in five different climate zones of Spain, i.e., A4 (very hot climate zones), B4 (hot climate zones), C4 (moderate climate zones), D3 (cold climate zones), and E1 (very cold climate zones). The authors accomplished a sensitivity analysis in order to identify the influence of passive strategies (i.e., with regard to solar reflectance) and renewable energy (i.e., with regard to aerothermal energy) on indoor temperatures and energy demands. The increment in indoor temperatures depends on the neighboring buildings so that effect of urban contexts as a source of protection against sunlight is also considered. The increment in the albedo (i.e., the solar reflectance) of the façade during the winter period produces little differences in indoor operative temperatures. On the contrary, during the summer period, it produces large temperature differences. Therefore, it is shown that colors significantly reduce temperatures from 1.24 to 3.04 °C, which means considerable annual energy savings. This research demonstrates that solar reflectance can reduce the air indoor operative temperature down to 4.16 °C during the month of May in the coldest climate zones. As a result of the simulations, it is noted that the coldest climate zones are influenced to a greater extent by the inclusion of their urban contexts in the simulations. However, the heating demand, without considering it, becomes lower. Therefore, ignoring the urban context produces important errors in the heating analysis (12.2% in the coldest climate zones) and also in the cooling analysis (39% in the hottest climate zones). Finally, the use of renewable energy in the configuration of a model with a high urban canyon (Hc), as well as with an east–west building orientation and a low albedo produces a difference of around 76% in the cooling costs within the hottest climate zones and around 73% in the heating costs within the coldest climate zones. The results of this study can be applied as a guideline in early architectural design.

Analysis and Comparison of Energy Efficiency Code Requirements for Buildings: A Morocco–Spain Case Study

“…The urban context was not included in this case example. Nevertheless, and in linewith [54], simulation in an urban context has a negative impact on the thermal energy demand, since higher values of the demand are usually obtained-i.e., an increment in kWh/m 2 . The initial different layers of materials were subsequently introduced according to the majority of the current Moroccan real estate and in line with the average prices based on the country's GDP.…”

A Comparison of Various Bottom-Up Urban Energy Simulation Methods Using a Case Study in Hangzhou, China

“…According to whether energy data is the only data type required for calculating urban energy consumption, this approach can be divided into statistical methods or other methods, and the statistical analysis method can be further classified into many sub-methods, such as the economic variables method and the physical variables method [31]. The bottom-up approach simulates urban energy consumption based on the calculated energy consumption of individual buildings within the area [32]; therefore, it can better reflect the spatial energy distribution and has a higher accuracy than the top-down approach [28]. Based on how the energy consumption of individual buildings is calculated, this approach can be further classified as a physical model method, data-driven model method, or hybrid model method [27], where the physical model method is used most commonly due to its transparency in modeling building energy consumption and its capability to link calculated urban energy simulation with urban morphological aspects, such as building archetypes.…”

The Relationship between the Use of Building Performance Simulation Tools by Recent Graduate Architects and the Deficiencies in Architectural Education

“…Other studies deal with the different uses of energy simulation by several users, particularly architects, and conclude that the use of technology could allow for a broader range of decisions [51]. While there are few empirical examples of the use of energy simulation by architects, recent studies explain how leading companies can develop know-how about the types and range of parameters to be handled by BPSTs [52][53][54].…”