Modeling of energy consumption is usually based on historical
consumption and the relationship of this consumption with other
relevant variables, such as economic, demographic, climatic indicators,
and such [2]. At present, energy modeling is a subject of widespread
interest among engineers and scientists concerned with the
problems of energy production and consumption [3]. Modeling in
some areas of application is now capable of making useful contributions
to planning and policy formulation [4]. In this regard,
energy planning is not possible without a reasonable knowledge
of the past and present energy-consumptions and likely future demands
[5]. Modeling and prediction of energy consumption play a
vital role in developed and developing countries for policy makers and related organizations. Underestimation of the consumption
would lead to potential outages that are devastating to life and
economy, whereas overestimation would lead to unnecessary idle
capacity which means wasted financial resources. Therefore, it
would be better to model electricity energy consumption with
good accuracy in order to avoid costly mistakes. Also, it is better
to use models that can handle nonlinearities among variables as
the expected nature of the energy consumption data is non-linear
[6].