Priority Weight-Based Systems to Predict Energy Consumption Behavior in Residential Buildings

As of 2020, an estimated 20% of energy was consumed by the residential sector. Different factors influence the energy usage of residential buildings. There are a significant number of studies to understand the implications of such factors on the energy consumption of domestic buildings. However, existing studies do not explicitly demonstrate the importance or connection between the variables. The objectives of this study are to determine the effectiveness of parameters that influence energy usage in residential concrete structures and to develop a priority weight-based system to determine energy consumption levels in residential buildings in developing tropical countries like Sri Lanka. In this study, the fuzzy analytical hierarchy process is utilized to develop the system by generating priority weights that account for parameter interrelationships and relevance. The novel identification system is developed considering four major parameters: building characteristics, characteristics of appliances and systems, characteristics of tenants' behavior, and climatic characteristics. These major factors are further divided into subcategories. The priority weights of parameters are calculated based on the input of 100 experts. The subjectivity of the developed system is eliminated by using numerical descriptors. The proposed model can predict energy consumption levels in residential buildings and identify the influence of factors affecting energy consumption. Understanding and modifying home energy consumption behaviors are effective in promoting energy efficiency and energy conservation.