Introduction

Abstract

For an export-oriented economy or an energy-limited economy, like Taiwan, economic development mainly depends on the supply level of electric energy; particularly, most production activities for each industry also depend on its available level. As the economic development is proceeding vigorously, the electric energy demand in industries, in commerce, and in people’s residential uses has also significantly increased. To ensure that electric energy is usable for all electricity users (i.e., meeting users’ demands) will be an important challenge for the electric energy industry. The availability and reliability of electric energy become the most premier issue in energy policy making. Therefore, accurate electric load forecasting is quite an important guide for effective implementations/actions of energy policies. The policy makers desire to look for founded forecasts to well plan the new electric power facilities investments and to determine the import and export amounts.KeywordsParticle Swarm OptimizationSupport Vector RegressionMean Absolute Percent ErrorGeneral Regression Neural NetworkLoad ForecastThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.