Análise sistêmica de indicadores de eficiência energética utilizando método AHP em escolas públicas classificadas por clusters

Abstract

This paper includes the initial stage of an energy pre diagnosis, which consists in the remote analysis of the consumption of electricity of public schools establishing indicators that directly assist in the process of choosing institutions able to carry out the implementation of energy efficiency programs in their facilities. The prospection took place electronically directly with the Department of Education of the State of Santa Catarina and with some Municipal Departments of Education. The sampling was 938 electricity bills, issued by the concessionaire from January 2017 to August 2018, belonging to 75 school units, located in 27 municipalities in the Midwest region of the State. The data collection and processing process used information presents on electricity bills with the structural characteristics of each educational institution, as well as operational protocols and the number of enrolments per class. Energy Efficiency Indicators were determined, based on the consumption ratio in kWh by the number of students, number of teachers and by built useful area, considering classrooms, computer labs, sports gymnasiums and cafeterias. The structure of the work was organized according to the Hierarchical Process Analysis method -AHP. The proposal of this work showed four clusters organized, such as the levels of human development index (HDI) of the municipalities involved, the respective places of installation in the urban perimeter or rural area, and the specification according to the three stages of the Law of Guidelines and Bases for Basic Education (early childhood education, elementary and high school) and the corresponding shifts of class (morning, evening and night) as well as their different combinations. This procedure measured missing terms by explaining the results in charts and tables. With this process it was possible to determine the average energy consumption of these school units according to similarities, as well as classify institutions that need energy efficiency actions as a priority. Some results showed that the least energy-efficient school in the region, according to the proposed indicators, is in the municipality with the highest HDI.