Assessment and Forecasting of Electric Load Demand of Don Honorio Ventura Technological State University

Careful management of energy consumption is indeed vital. Energy consumption can be effectively managed, if it is accurately quantified; this allows the development of awareness on how much energy is being consumed within an institution, residence or industrial facility. The amount of expenditure on electric usage gives pressure to the institution’s operation and maintenance especially on state universities and colleges that are given tight budget allocation by the government per year. This study aims to assess the present and future electric load demand of Don Honorio Ventura Technological State University-Main Campus. The study had used Time Series Analysis and Nonlinear Model to evaluate energy consumption. Medium –term forecasting was considered and was analyzed using data analysis toolpak of Microsoft Excel 2013 for statistical treatment and Matlab R2015 for forecasting. Results show that the month of July has the highest percentage of energy consumption of 11% while the months of January and April have the least percentage of 6%. Exponential regression model was used because of its good result on cross validation, low RMSE value of 4.1 0e4, and high R squared value of 0.9778. The highest percentage energy consumption was observed from electric meter number 130. The researchers find the need to conduct different models in electric load demand forecasting and proper identification of loads per building is suggested.