APPLICATION OF MATHEMATICAL EQUATIONS TO FORECAST ELECTRICITY CONSUMPTION FOR ENERGY MANAGEMENT IN UNIVERSITIES: A CASE STUDY OF UTTARADIT RAJABHAT UNIVERSITY

Abstract

The objective of this research is to apply and test mathematical equations for volume forecasting the electricity usage at Uttaradit Rajabhat University using 7 factors; 1) number of buildings, 2) building usable area (square meters), 3) number of air conditioners, 4) number of light bulbs, 5) number of students, 6) number of teachers and personnel, and 7) amount of energy use during the time span of 6 years (2018-2023) and applying 4 equations which were 1) Trend prediction equation (Trend P.), 2) Simple moving average equation (SMA), 3) Exponential equation Adaptive one layer (ARRSES), and 4) Exponential weighted moving average (EWMA) equations. The research results revealed that when testing the mathematical equation by bringing monthly data into the equation, EWMA had the least error with an average of 15.20 percent, followed by the ARRSES equation with an average error of 18.15 percent, Trend P equation had the average error of 18.59 percent, and the SMA equation had an average error of 19.98 percent. When the annual average data was used with the equation, it was found that the Trend P. equation had the least error of 6.40 percent, while the other equations had more than 25 percent of error. Therefore, it could be concluded that the appropriate equation for forecasting electricity use should be the Trend P. equation combined with annual data. This was because the data set used was linear, Trend P. is the most appropriate. When the above equation is applied for forecasting together with annual electricity usage data of Uttaradit Rajabhat University in 2023, it is found that in 2024 - 2026 there will be an increase in the amount of electricity used. 5.57 percent, 6.37 percent, and 12.23 percent, respectively. If there is no use of alternative energy or energy management policy As a result, in 2026, Uttaradit Rajabhat University will have an electricity consumption of 7,525,959 kilowatt-hours. Or calculate the electricity cost that must be paid 36,801,939 baht per year by calculating the electricity cost of 4.89 baht per unit from the total average electricity cost from Value Added Tax (VAT) plus the automatic electricity rate adjustment (Ft) from the year 2018 – 2023. Therefore, the application of the above mathematical equations can predict the electricity consumption of Uttaradit Rajabhat University. As a result, the university can use the data to formulate appropriate policies for energy management in the university.