Abstract

In Mexico, buildings' deficient thermal performance is one of the leading causes of the intensive use of energy. This research analyzes the perspective of energy demand required to meet the cooling needs in the country through the Weather-based technical indexes: Cooling Degree Hour (CDH) and Operation Hours (OH). The study considered the 2440 municipalities that make up the 32 states of the Mexican Republic and three chronological progressions throughout the 21st century (2020, 2050, and 2100). Meteorological data was collected through the Meteonorm software considering climate change projections, precisely two Representative Concentration Pathway scenarios (RCP 4.5 - Intermediate) and (RCP 8.5 - High). Based on the calculations, spatial and temporal panoramas of the behavior of air conditioning hours under various target temperatures (20 °C, 23 °C, and 26 °C) were established. Taking the most important type of housing in Mexico (Social Interest Housing) as a case study, a database of air conditioning energy demand was performed and subsequently grouped the states according to cluster similarities. The results show that >50 % of the Mexican Republic requires high air conditioning levels. The maximum CDH for 2100-RCP 8.5 will be 70 % higher than currently needed. Even for the year 2050-RCP8.5, an increase of >40 % of CDH was obtained. Regarding the OH, the results show an increase of >50 % concerning the current behavior of the country. Regardless of the scenario, the range of operating hours with the highest operating requirements is between 11 am and 4 pm, peaking in the summer season. The simulations showed that some Mexican regions exceed 12,000 kWh in air conditioning. An increase of 20 % and 35 % is expected for the years 2050 and 2100. The simulations showed that a considerable percentage of Mexico exceeds 12,000 kWh in air conditioning, while by 2050 and 2100, this consumption will increase by 20 % and 35 %, respectively. Based on these results, the first classification of groups in energy demand was generated, allowing a focus on energy efficiency strategies to obtain net zero Buildings. The data obtained shows that relative humidity is a variable that affects the increase in energy consumption in refrigeration and simplifies the process of classifying regions with similar patterns in air conditioning.