Energy Consumption Forecasting Model for Puerto Princesa Distribution System Using Multiple Linear Regression


Authors : Alfred Rey G. Vasquez; Michael Ernie F. Rodriguez; Roy C. Dayupay

Volume/Issue : Volume 5 - 2020, Issue 11 - November

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/3lqDzTm

Power system engineers widely consider electric load forecasting because of its vital role in economically optimizing and securing the efficient operation of the power system. A forecast can be utilized by electric utilities to upgrade and improve the existing distribution facilities. Also, through this prediction, future developments could be planned concerning generation and transmission facilities. In this paper, the annual energy consumption of the Puerto Princesa Distribution System for the year 2019-2028 was forecasted using multiple linear regression. The peak demand and the number of consumers were the variables considered for the regression analysis. From the error performance test, the results indicate that multiple linear regression is a useful technique for long-term load forecasting, having a minimum percent error. Based on the regression results, the energy consumption by 2028 is expected to be 566,078,019.1 kWh. The error performance test demonstrates that the mean average percent error of 0.74% which indicates that the multiple linear regression model is a good fit

Keywords : Distribution System, Energy Consumption Forecasting, Long-Term Forecast, Multiple Linear Regression.

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