Forecasting the Electricity Consumption in a Higher Education Institution
Abstract The objective of this paper is to present a mathematical representation by Regression Analysis that enables the projection of electricity consumption according to the built area and population in Higher Education Institutions (HEI) and to define an Indicator that contemplates the most significant variable in consumption. of electric power. The Null Hypothesis -H0 is that in a HEI the most appropriate indicator is the Kilo Watt Hour per square meter (kWh / m2) as proposed by the Ministry of Planning and Management - MP. The research universe is 2,368 HEI, identified in a report from the Ministry of Education (2015). As Sample and case study, data from the thirteen Campi of the Federal Technological University of Paraná (UTFPR) are used. As a computational tool we use the IBM SPSS Statistics Base Software for Windows version 23 from SPSS Inc .. For the considered Sample and research design, the conclusion is that the null hypothesis is rejected accepting that the most significant indicator is the kilo. Watt Time per user (kWh / user). This conclusion does not exclude the relationship between constructed area and Energy Consumption, but reveals that it is not as significant as the number of individuals in HEI for this sample.
| Main Authors: | , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Instituto de Tecnologia do Paraná - Tecpar
2019
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132019000200203 |
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| Summary: | Abstract The objective of this paper is to present a mathematical representation by Regression Analysis that enables the projection of electricity consumption according to the built area and population in Higher Education Institutions (HEI) and to define an Indicator that contemplates the most significant variable in consumption. of electric power. The Null Hypothesis -H0 is that in a HEI the most appropriate indicator is the Kilo Watt Hour per square meter (kWh / m2) as proposed by the Ministry of Planning and Management - MP. The research universe is 2,368 HEI, identified in a report from the Ministry of Education (2015). As Sample and case study, data from the thirteen Campi of the Federal Technological University of Paraná (UTFPR) are used. As a computational tool we use the IBM SPSS Statistics Base Software for Windows version 23 from SPSS Inc .. For the considered Sample and research design, the conclusion is that the null hypothesis is rejected accepting that the most significant indicator is the kilo. Watt Time per user (kWh / user). This conclusion does not exclude the relationship between constructed area and Energy Consumption, but reveals that it is not as significant as the number of individuals in HEI for this sample. |
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